OCR for DjVu

Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts

Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout

CCpdf: Building a High Quality Corpus for Visually Rich Documents from
  Web Crawl Data


ClaSPy: A Python package for time series segmentation.

ClaSP - Time Series Segmentation

PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, CIKM 2021

ClaSP: parameter-free time series segmentation

Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark


TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"

Random Search and Reproducibility for Neural Architecture Search

Task Transfer by Preference-Based Cost Learning

NAS evaluation is frustratingly hard

TextNAS: A Neural Architecture Search Space tailored for Text Representation

BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture

IEEE transactions on neural networks and learning systems

Towards Oracle Knowledge Distillation with Neural Architecture Search

A Study of the Learning Progress in Neural Architecture Search
  Techniques

Long-term Reproducibility for Neural Architecture Search


Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)

Neural Attention Distillation: Erasing Backdoor Triggers from Deep
  Neural Networks

Anti-Backdoor Learning: Training Clean Models on Poisoned Data

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information

Backdoor Defense via Deconfounded Representation Learning


Official code release for ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity (published at ICLR 2022)

Composing Text and Image for Image Retrieval - An Empirical Odyssey

Automatic Spatially-aware Fashion Concept Discovery

Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models


Code for Multi-Object Matching

Multi-Image Semantic Matching by Mining Consistent Features

Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian

State of the Art and Potentialities of Graph-level Learning

Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching


Code for GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation (SIGIR 2020)

PROCEEDINGS OF THE 43RD INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '20)

ConsRec: Learning Consensus Behind Interactions for Group Recommendation

Deep Reinforcement Learning based Group Recommender System

Sparsity-aware neural user behavior modeling in online interaction
  platforms


Please choose the openseg.pytorch project for the updated code that achieve SOTA on 6 benchmarks!

OCNet: Object Context Network for Scene Parsing

SegFix: Model-Agnostic Boundary Refinement for Segmentation

Interlaced Sparse Self-Attention for Semantic Segmentation


Code for "Proximal Distilled Evolutionary Reinforcement Learning", accepted at AAAI 2020

THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

ERL-Re^2: Efficient Evolutionary Reinforcement Learning with Shared
  State Representation and Individual Policy Representation

Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation

A surrogate-assisted controller for expensive evolutionary reinforcement learning


A GAN experiment that, given an image of a letter, produces an alphabet in the same style.

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Improved Training of Wasserstein GANs

GlyphGAN: Style-consistent font generation based on generative adversarial networks


Classification and Gradient-based Localization of Chest Radiographs using PyTorch.

Deep Residual Learning for Image Recognition

Very Deep Convolutional Networks for Large-Scale Image Recognition

Densely Connected Convolutional Networks

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

International journal of computer vision


GNNExplainer: Generating Explanations for Graph Neural Networks

Task-Agnostic Graph Explanations

[Re] Parameterized Explainer for Graph Neural Network

Efficient GNN Explanation via Learning Removal-based Attribution

GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers
  through In-depth Benchmarking

Faithful Explanations for Deep Graph Models


Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Evaluating Bayesian Deep Learning Methods for Semantic Segmentation

Loss-Calibrated Approximate Inference in Bayesian Neural Networks


An implementation FGNN.

A Survey on Session-based Recommender Systems

Global Context Enhanced Graph Neural Networks for Session-based Recommendation

Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM '19)

Graph Learning based Recommender Systems: A Review

Exploiting Graph Structured Cross-Domain Representation for Multi-Domain
  Recommendation


Code and data for paper "Embedding Uncertain Knowledge Graphs"

Embedding Uncertain Knowledge Graphs

Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes

Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning


Codes accompanying the paper "DOP: Off-Policy Multi-Agent Decomposed Policy Gradients" (ICLR 2021, https://arxiv.org/abs/2007.12322)

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Value-Decomposition Networks For Cooperative Multi-Agent Learning

Multiagent Cooperation and Competition with Deep Reinforcement Learning

Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients.


PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023

Describing Textures in the Wild

The iNaturalist Species Classification and Detection Dataset

How to Exploit Hyperspherical Embeddings for Out-of-Distribution
  Detection?

Nearest Neighbor Guidance for Out-of-Distribution Detection


Bounding box detection of drones (small scale quadcopters) with CNTK Fast R-CNN

Deep Learning on Multi Sensor Data for Counter UAV Applications—A Systematic Review

Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges

Drone Detection and Tracking in Real-Time by Fusion of Different Sensing Modalities


A list of our publications.

Is Machine Learning Ready for Traffic Engineering Optimization?

RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation

RouteNet-Fermi: Network Modeling With Graph Neural Networks

MAGNNETO: A Graph Neural Network-Based Multi-Agent System for Traffic Engineering

IEEE transactions on cognitive communications and networking/IEEE Transactions on Cognitive Communications and Networking


Ultra-efficient taxonomic mapping of NGS data

taxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time

Feeding strategy shapes gut metagenomic enrichment and functional specialization in captive lemurs

Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses


3D airway segmentation method

Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation


Learning Facial Representations from the Cycle-consistency of Face (ICCV 2021)

Self-supervised learning of a facial attribute embedding from video

Unsupervised Learning of Face Representations


Remote Sensing Image Classification Benchmark for Deep Learning

RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data

RS-DARTS: A Convolutional Neural Architecture Search for Remote Sensing Image Scene Classification

Data Fusion in Earth Observation and the Role of Citizen as a Sensor: A Scoping Review of Applications, Methods and Future Trends

Large-Scale, Multiple Level-of-Detail Change Detection from Remote Sensing Imagery Using Deep Visual Feature Clustering

On the Selective and Invariant Representation of DCNN for High-Resolution Remote Sensing Image Recognition


Repository for research works and resources related to model reprogramming <https://arxiv.org/abs/2202.10629>

Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning

Adversarial Reprogramming of Pretrained Neural Networks for Fraud Detection

An Improved (Adversarial) Reprogramming Technique for Neural Networks

Reprogramming GANs via Input Noise Design

MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2020, PT II


A custom Rouge wrapper for summary evaluation.

BRIO: Bringing Order to Abstractive Summarization

A Joint Model of Conversational Discourse and Latent Topics on Microblogs

Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality

Balancing Lexical and Semantic Quality in Abstractive Summarization


Conditional Theorem Proving

Differentiable Reasoning on Large Knowledge Bases and Natural Language

Learning Reasoning Strategies in End-to-End Differentiable Proving

Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks


Data and Code Release for "On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries"

Awakening Latent Grounding from Pretrained Language Models for Semantic Parsing

Leveraging Explicit Lexico-logical Alignments in Text-to-SQL Parsing

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)


Data plus code fo Classification of Heart Sound Signal Using Multiple Features

Deep Layer Kernel Sparse Representation Network for the Detection of Heart Valve Ailments from the Time-Frequency Representation of PCG Recordings

Transfer Learning Models for Detecting Six Categories of Phonocardiogram Recordings

Journal of cardiovascular development and disease

Automatic Detection and Classification of Cardiovascular Disorders Using Phonocardiogram and Convolutional Vision Transformers

Deep Learning Algorithm for Heart Valve Diseases Assisted Diagnosis

Heart Sound Classification Network Based on Convolution and Transformer


A fast approximation to a Dirichlet Process Mixture model (DPM) for clustering genetic data

ModelFinder: fast model selection for accurate phylogenetic estimates

phytools: an R package for phylogenetic comparative biology (and other things)

ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data

Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software

Fast hierarchical Bayesian analysis of population structure

Shiga toxin-producing Escherichia coli clonal complex 32, including serotype O145:H28, in the UK and Ireland


Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition

Sample-Guided Adaptive Class Prototype for Visual Domain Adaptation


Code and datasets for EMNLP2018 paper ‘‘Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification’’.

Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training

Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning

Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis

Domain Confused Contrastive Learning for Unsupervised Domain Adaptation

DaMSTF: Domain Adversarial Learning Enhanced Meta Self-Training for Domain Adaptation

Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification


The code for paper MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation

Task-adaptive Neural Process for User Cold-Start Recommendation

Enhancing Factorization Machines with Generalized Metric Learning

Cross-Domain Meta-Learner for Cold-Start Recommendation

IEEE transactions on knowledge and data engineering


HyperSpectral Salient Object Detection Dataset

Hyperspectral Image Dataset for Benchmarking on Salient Object Detection

Salient object detection on hyperspectral images using features learned
  from unsupervised segmentation task

Salient target detection in hyperspectral image based on visual attention

CNN-Based Salient Object Detection on Hyperspectral Images Using Extended Morphology

IEEE geoscience and remote sensing letters

Tensor-Based Sketching Method for the Low-Rank Approximation of Data
  Streams


A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series

Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability

Proceedings of the 31st ACM International Conference on Information & Knowledge Management


Matlab implementation of multi-view low-rank sparse subspace clustering

Multi-view low-rank sparse subspace clustering

Latent Complete Row Space Recovery for Multi-View Subspace Clustering

Unpaired Multi-View Graph Clustering with Cross-View Structure Matching


VulRepair: A T5-Based Automated Software Vulnerability Repair

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Neural Transfer Learning for Repairing Security Vulnerabilities in C Code

A Survey of Learning-based Automated Program Repair


[CVPR2019] NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction

Learning twofold heterogeneous multi-task by sharing similar convolution kernel pairs

Learning multi-tasks with inconsistent labels by using auxiliary big task


A comparison of different Oxford Nanopore basecallers

Performance of neural network basecalling tools for Oxford Nanopore sequencing

Genetic Biomonitoring and Biodiversity Assessment Using Portable Sequencing Technologies: Current Uses and Future Directions

Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford Nanopore MinION sequencer

Completing Circular Bacterial Genomes With Assembly Complexity by Using a Sampling Strategy From a Single MinION Run With Barcoding

poreTally: run and publish de novo nanopore assembler benchmarks


Using modified BiSeNet for face parsing in PyTorch

What makes fake images detectable? Understanding properties that generalize

M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection

Content-Aware GAN Compression

Gender Slopes: Counterfactual Fairness for Computer Vision Models by Attribute Manipulation

Learning to Relight Portrait Images via a Virtual Light Stage and Synthetic-to-Real Adaptation

Gendered Differences in Face Recognition Accuracy Explained by Hairstyles, Makeup, and Facial Morphology

IEEE transactions on information forensics and security

Is Face Recognition Sexist? No, Gendered Hairstyles and Biology Are

Making Robots Draw A Vivid Portrait In Two Minutes

Face Recognition Accuracy Across Demographics: Shining a Light Into the Problem

MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network


Improving Neural Machine Translation Models with Monolingual Data

Learning to Paraphrase for Question Answering

Abu-MaTran at WMT 2016 Translation Task: Deep Learning, Morphological Segmentation and Tuning on Character Sequences

Proceedings of the First Conference on Machine Translation: Volume 2,
          Shared Task Papers


NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks

Dynamic Network Embedding Survey

Understanding graph embedding methods and their applications

F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams


Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)

Time Series Change Point Detection with Self-Supervised Contrastive Predictive Coding

InDiD: Instant Disorder Detection via Representation Learning

Learning Sinkhorn divergences for supervised change point detection


PyTorch implementation of over 30 realtime semantic segmentations models, e.g. BiSeNetv1, BiSeNetv2, CGNet, ContextNet, DABNet, DDRNet, EDANet, ENet, ERFNet, ESPNet, ESPNetv2, FastSCNN, ICNet, LEDNet, LinkNet, PP-LiteSeg, SegNet, ShelfNet, STDC, SwiftNet, and support knowledge distillation, distributed training etc.

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Distilling the Knowledge in a Neural Network

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

Visual Communications and Image Processing

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

Rethinking BiSeNet For Real-time Semantic Segmentation


On-Premise DeepFake Detection SDK for Linux

FaceForensics++: Learning to Detect Manipulated Facial Images

Taming Transformers for High-Resolution Image Synthesis

MesoNet: a Compact Facial Video Forgery Detection Network

International Workshop on Information Forensics and Security

Unmasking DeepFakes with simple Features

Rethinking the Up-Sampling Operations in CNN-based Generative Network
  for Generalizable Deepfake Detection


Representation Learning and Representation Fusion for computer vision, semantic scene understanding, and robotics.

Representation Learning: A Review and New Perspectives

RSSFormer: Foreground Saliency Enhancement for Remote Sensing Land-Cover Segmentation

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation

Wave-Like Class Activation Map With Representation Fusion for Weakly-Supervised Semantic Segmentation


:eyes: DeepSeeNet is a deep learning framework for classifying patient-based age-related macular degeneration severity in retinal color fundus photographs.

DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs

A deep learning approach for automated detection of geographic atrophy from color fundus photographs

A multi-task deep learning model for the classification of Age-related Macular Degeneration


Constituency Parsing with a Self-Attentive Encoder

Multilingual Constituency Parsing with Self-Attention and Pre-Training

Learned Incremental Representations for Parsing

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)


A benchmarking suite for disentanglement algorithms, suited for evaluating robustness to correlated factors. Codebase for the paper "Disentanglement of Correlated Factors via Hausdorff Factorized Support" by Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt.

Auto-Encoding Variational Bayes

Deep Learning Face Attributes in the Wild

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Disentangling by Factorising

Isolating Sources of Disentanglement in Variational Autoencoders

Understanding disentangling in β-VAE

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

Learning to Generate Chairs, Tables and Cars with Convolutional Networks

Weakly-Supervised Disentanglement Without Compromises

Learning Deep Disentangled Embeddings with the F-Statistic Loss


MUM&Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (only v4) to detect Structural Variation

MUM&Co: accurate detection of all SV types through whole-genome alignment

Molecular profiling of beer wort fermentation diversity across natural Saccharomyces eubayanus isolates

Telomere-to-telomere assemblies of 142 strains characterize the genome structural landscape in Saccharomyces cerevisiae


Dogs classification with Deep Metric Learning

FaceNet: A Unified Embedding for Face Recognition and Clustering

No Fuss Distance Metric Learning using Proxies

SoftTriple Loss: Deep Metric Learning Without Triplet Sampling

Proxy Anchor Loss for Deep Metric Learning

A new dataset of dog breed images and a benchmark for finegrained classification


End-to-End Low Cost Compressive Spectral Imaging with Spatial-Spectral Self-Attention

Snapshot Compressive Imaging: Theory, Algorithms, and Applications

Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging


The source code of ISWC2020 paper "Temporal Knowledge Graph completion based on time series Gaussian embedding " and COLING2020 paper "TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation "

Temporal Knowledge Graph Embedding Model based on Additive Time Series
  Decomposition

Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings

North American Chapter of the Association for Computational Linguistics

RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion

Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures

Few-Shot Inductive Learning on Temporal Knowledge Graphs using
  Concept-Aware Information

ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations


RISC-V CPU Core (RV32IM)

Don't CWEAT It

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design


OCR-VQGAN, a discrete image encoder (tokenizer and detokenizer) for figure images in Paper2Fig100k dataset. Implementation of OCR Perceptual loss for clear text-within-image generation. Fork from VQGAN in CompVis/taming-transformers

High-Resolution Image Synthesis with Latent Diffusion Models

Taming Transformers for High-Resolution Image Synthesis

Character Region Awareness for Text Detection

OCR-VQGAN: Taming Text-within-Image Generation

FigGen: Text to Scientific Figure Generation


A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

International Conference on Information and Knowledge Management

Graph-based Semi-supervised Learning: A Comprehensive Review

Predicting Attributes of Nodes Using Network Structure

ACM transactions on intelligent systems and technology

Seven-Layer Model in Complex Networks Link Prediction: A Survey


Logiqa2.0 dataset - logical reasoning in MRC and NLI tasks

LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Transforming Question Answering Datasets Into Natural Language Inference Datasets

Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4


assembler for NVIDIA FERMI. Imported from Google Code

Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking.

Dissecting the NVidia Turing T4 GPU via Microbenchmarking


Implementation of various Distributional Reinforcement Learning Algorithms using TensorFlow2.

A Distributional Perspective on Reinforcement Learning

Distributional Reinforcement Learning with Quantile Regression

Implicit Quantile Networks for Distributional Reinforcement Learning


Code for "Planning Goals for Exploration", ICLR2023 Spotlight. An unsupervised RL agent for hard exploration tasks.

Skew-Fit: State-Covering Self-Supervised Reinforcement Learning

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning

Discovering and Achieving Goals via World Models

Planning Goals for Exploration


Investigating Impaired Aircraft's Flight Envelope Variation Predictability Using Least-Squares Regression Analysis

Journal of aerospace information systems

Nonlinear Trajectory-Based Region of Attraction Estimation for Aircraft Dynamics Analysis


RepBERT is a competitive first-stage retrieval technique. It represents documents and queries with fixed-length contextualized embeddings. The inner products of them are regarded as relevance scores. Its efficiency is comparable to bag-of-words methods.

RepBERT: Contextualized Text Embeddings for First-Stage Retrieval

Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently

Hard Negatives or False Negatives: Correcting Pooling Bias in Training Neural Ranking Models


Library for the training and evaluation of object-centric models (ICML 2022)

Generalization and Robustness Implications in Object-Centric Learning

Robust and Controllable Object-Centric Learning through Energy-based
  Models


Deep-Atrous-CNN-Text-Network: End-to-end word level model for sentiment analysis and other text classifications

Convolutional Neural Networks for Sentence Classification

WaveNet: A Generative Model for Raw Audio

Neural Machine Translation in Linear Time


Code for the paper Implicit Weight Uncertainty in Neural Networks

Quality of Uncertainty Quantification for Bayesian Neural Network Inference

Uncertainty-Aware Deep Classifiers using Generative Models

Projected BNNs: Avoiding weight-space pathologies by learning latent
  representations of neural network weights

Graceful Degradation and Related Fields


Code for Federated Learning with Matched Averaging, ICLR 2020.

FedLab: A Flexible Federated Learning Framework

Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation.

Federated Learning with Position-Aware Neurons


[CVPR 2022] StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2

Temporal Generative Adversarial Nets with Singular Value Clipping

Towards Accurate Generative Models of Video: A New Metric & Challenges

MoStGAN-V: Video Generation with Temporal Motion Styles

SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models

MOSO: Decomposing MOtion, Scene and Object for Video Prediction

ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation


Author's PyTorch implementation of TD3 for OpenAI gym tasks

Addressing Function Approximation Error in Actor-Critic Methods

An Optimistic Perspective on Offline Reinforcement Learning

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion

CEM-RL: Combining evolutionary and gradient-based methods for policy search

Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics

Better Exploration with Optimistic Actor-Critic

Quasi-hyperbolic momentum and Adam for deep learning

Deep Reinforcement Learning for Indoor Mobile Robot Path Planning

Learning Self-Imitating Diverse Policies


Cartesian Cubical Type Theory

Cubical Agda: A dependently typed programming language with univalence and higher inductive types

Proceedings of the ACM on programming languages

Internal Universes in Models of Homotopy Type Theory

Higher inductive types in cubical computational type theory

Internalizing Representation Independence with Univalence

Cubical Syntax for Reflection-Free Extensional Equality

Computational Higher Type Theory IV: Inductive Types

Decomposing the Univalence Axiom

Model structure on the universe of all types in interval type theory

Naive cubical type theory

The derivator of setoids


A Stan-like probabilistic programming language.

Probabilistic programming with densities in SlicStan: efficient, flexible, and deterministic

Conditional Independence by Typing

Program Analysis of Probabilistic Programs


Official repository of CVPR 2020 paper "On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location"

Deep Residual Learning for Image Recognition

Natural Adversarial Examples

Working hard to know your neighbor's margins: Local descriptor learning loss

Unveiling The Mask of Position-Information Pattern Through the Mist of
  Image Features

Knowledge Transferred Fine-Tuning: Convolutional Neural Network Is Born Again With Anti-Aliasing Even in Data-Limited Situations


[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness

Truncated Affinity Maximization: One-class Homophily Modeling for Graph
  Anomaly Detection

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation


Combined genomic, transcriptomic, and metabolomic analyses provide insights into chayote (Sechium edule) evolution and fruit development

The genome and transcriptome analysis of snake gourd provide insights into its evolution and fruit development and ripening

Chromosome-level assembly and analysis of the Thymus genome provide insights into glandular secretory trichome formation and monoterpenoid biosynthesis in thyme

Chromosome-level genome assembly of Aristolochia contorta provides insights into the biosynthesis of benzylisoquinoline alkaloids and aristolochic acids

Genome structure-based Juglandaceae phylogenies contradict alignment-based phylogenies and substitution rates vary with DNA repair genes

Vulture Genomes Reveal Molecular Adaptations Underlying Obligate Scavenging and Low Levels of Genetic Diversity

Chromosome-level genome assembly of an endangered plant Prunus mongolica using PacBio and Hi-C technologies

DNA research : an international journal for rapid publication of reports on genes and genomes

Chromosome-scale genomics, metabolomics, and transcriptomics provide insight into the synthesis and regulation of phenols in Vitis adenoclada grapes

Chromosome-level genome and multi-omics analyses provide insights into the geo-herbalism properties of Alpinia oxyphylla


power systems tools made beautiful


[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation

PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

Prior Guided Feature Enrichment Network for Few-Shot Segmentation

Part-aware Prototype Network for Few-shot Semantic Segmentation


This is the implementation of our Interspeech 2021 paper: Limited data emotional voice conversion leveraging text-to-speech: two-stage sequence-to-sequence training.

Limited Data Emotional Voice Conversion Leveraging Text-to-Speech:
  Two-stage Sequence-to-Sequence Training

An Overview & Analysis of Sequence-to-Sequence Emotional Voice Conversion

EmoFake: An Initial Dataset for Emotion Fake Audio Detection


Pytorch implementation of the Power Spherical distribution

The Power Spherical distribution

Representation Uncertainty in Self-Supervised Learning as Variational Inference

Latent SDEs on Homogeneous Spaces


Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification

Sparse Graph Attention Networks

Robust Preference-Guided Denoising for Graph based Social Recommendation

Data Augmentation on Graphs: A Technical Survey

Adversarially Robust Neural Architecture Search for Graph Neural Networks

Combating Bilateral Edge Noise for Robust Link Prediction

Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification

Data Augmentation for Graph Data: Recent Advancements

A Comparative Study on Robust Graph Neural Networks to Structural Noises

Revisiting Signed Propagation for Multi-Class Graph Neural Networks


Appraise evaluation system for manual evaluation of machine translation output

Findings of the 2016 Conference on Machine Translation

Meeting of the Association for Computational Linguistics

Findings of the 2014 Workshop on Statistical Machine Translation

Achieving Human Parity on Automatic Chinese to English News Translation

Findings of the 2019 Conference on Machine Translation (WMT19)

S(+)-ketamine for control of perioperative pain and prevention of post thoracotomy pain syndrome: a randomized, double-blind study.

Findings of the 2015 Workshop on Statistical Machine Translation

Ground Truth for Grammatical Error Correction Metrics

PROCEEDINGS OF THE 53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL) AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (IJCNLP), VOL 2

Attaining the Unattainable? Reassessing Claims of Human Parity in Neural
  Machine Translation

A Set of Recommendations for Assessing Human-Machine Parity in Language Translation

Journal of artificial intelligence research/The journal of artificial intelligence research

What Level of Quality can Neural Machine Translation Attain on Literary
  Text?


Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them


Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation

Object-aware Inversion and Reassembly for Image Editing


Open Network-Enabled Flux processing pipeline

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Ideas and perspectives: enhancing the impact of the FLUXNET network of eddy covariance sites

Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes

Standardized flux seasonality metrics: A companion dataset for FLUXNET annual product


Implementation for Simple Spectral Graph Convolution in ICLR 2021

Simple Spectral Graph Convolution

International Conference on Learning Representations

Node Dependent Local Smoothing for Scalable Graph Learning


Source Code for IJCAI'20 "KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction"

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization

Graph-based Molecular Representation Learning

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural
  Network with Biomedical Network


Train bilingual embeddings as described in our NAACL 2015 workshop paper "Bilingual Word Representations with Monolingual Quality in Mind". Besides, it has all the functionalities of word2vec with added features and code clarity. See README for more info.

GLUECoS : An Evaluation Benchmark for Code-Switched NLP

Word Embeddings for Code-Mixed Language Processing

Empirical Methods in Natural Language Processing

Modeling Code-Switch Languages Using Bilingual Parallel Corpus

Fully Unsupervised Crosslingual Semantic Textual Similarity Metric Based on BERT for Identifying Parallel Data

Conference on Computational Natural Language Learning

Variable Mini-Batch Sizing and Pre-Trained Embeddings

Proceedings of the Second Conference on Machine Translation

Unsupervised Joint Training of Bilingual Word Embeddings

Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora

Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings

Learning to translate from graded and negative relevance information

International Conference on Computational Linguistics


OpenNI

The SPHERE Challenge Activity Recognition with Multimodal Sensor Data

Probabilistic Sensor Fusion for Ambient Assisted Living

Markerless 3D Interaction in an Unconstrained Handheld Mixed Reality Setup

The international journal of virtual reality/The International journal of virtual reality

Dialectical polyptych: an interactive movie


Source code and demos for "Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning"

Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets

IEEE journal of biomedical and health informatics

Towards Knowledge Uncertainty Estimation for Open Set Recognition

Machine learning and knowledge extraction

A Lightweight Convolutional Neural Network for Bacterial Identification Based on Raman Spectra

RamanNet: a generalized neural network architecture for Raman spectrum analysis


[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

Pruning Filters for Efficient ConvNets

Trainability Preserving Neural Pruning

Why is the State of Neural Network Pruning so Confusing? On the
  Fairness, Comparison Setup, and Trainability in Network Pruning


PyTorch implementation of realNVP

Density estimation using Real NVP

The Gaussian equivalence of generative models for learning with two-layer neural networks

Diffeomorphic Counterfactuals with Generative Models


Variational Autoencoder with Arbitrary Conditioning

Missing Data Imputation using Optimal Transport

Flow Models for Arbitrary Conditional Likelihoods

Conditional Generative Model Based Predicate-Aware Query Approximation

THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network

Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features

Missingness Augmentation: A General Approach for Improving Generative Imputation Models


This is the PyTorch implementation of VGG network trained on CIFAR10 dataset

Explanations can be manipulated and geometry is to blame

Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters

Learning Low-Rank Approximation for CNNs

A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients

Do Perceptually Aligned Gradients Imply Adversarial Robustness?

Orthogonal Deep Models As Defense Against Black-Box Attacks

Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise


MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space

Describing Textures in the Wild

The iNaturalist Species Classification and Detection Dataset

LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning


A flexible, scalable, and reproducible pipeline to automate variant calling from sequence reads.

grenepipe: a flexible, scalable and reproducible pipeline to automate variant calling from sequence reads

Monitoring rapid evolution of plant populations at scale with Pool-Sequencing

grenepipe: A flexible, scalable, and reproducible pipeline to automate variant and frequency calling from sequence reads


Official implementation in PyTorch of SASNet as described in "To Choose or to Fuse? Scale Selection for Crowd Counting"

Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework

THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

Uniformity in Heterogeneity: Diving Deep into Count Interval Partition for Crowd Counting


(ICCV 2019) Uncertainty-aware Face Representation and Recognition

Probabilistic Face Embeddings

SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance

Mitigating dataset harms requires stewardship: Lessons from 1000 papers

CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

Canonical Face Embeddings

Improving the Head Pose Variation Problem in Face Recognition for Mobile Robots


The source code of NIPS17 'Universal Style Transfer via Feature Transforms'.

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

Fast Patch-based Style Transfer of Arbitrary Style

Optimal Whitening and Decorrelation

Neural Comic Style Transfer: Case Study

Two-stream FCNs to balance content and style for style transfer


openXBOW - the Passau Open-Source Crossmodal Bag-of-Words Toolkit

AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit

Classification of Speech with and without Face Mask using Acoustic Features

Nkululeko: A Tool For Rapid Speaker Characteristics Detection

LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION


Benchmarks for Deep Off-Policy Evaluation

Variational Latent Branching Model for Off-Policy Evaluation


Algorithms for Privacy-Preserving Machine Learning in JAX

Unlocking High-Accuracy Differentially Private Image Classification
  through Scale

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy

Unlocking Accuracy and Fairness in Differentially Private Image
  Classification

Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models


A Closer Look at Accuracy vs. Robustness

SOAR: Second-Order Adversarial Regularization

Augment then Smooth: Reconciling Differential Privacy with Certified
  Robustness


Investigating Capsule Networks with Dynamic Routing for Text Classification

A Survey on Text Classification: From Shallow to Deep Learning

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications

Fast Dynamic Routing Based on Weighted Kernel Density Estimation


Named Entity Recognition as Dependency Parsing

A Unified Generative Framework for Various NER Subtasks

Rethinking Negative Sampling for Handling Missing Entity Annotations

A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends

Segmenting Natural Language Sentences via Lexical Unit Analysis

Priberam Labs at the 3rd Shared Task on SlavNER

Workshop on Balto-Slavic Natural Language Processing


Official Code for our MICCAI 2022 paper "Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation"

Rethinking Semi-Supervised Medical Image Segmentation: A
  Variance-Reduction Perspective


PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)

Mean-Shifted Contrastive Loss for Anomaly Detection

Attribute-based Representations for Accurate and Interpretable Video
  Anomaly Detection

SLA^2P: Self-supervised Anomaly Detection with Adversarial Perturbation


Deep Learning on a Data Diet: Finding Important Examples Early in Training

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular
  data

The Details Matter: Preventing Class Collapse in Supervised Contrastive Learning

AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD)

Coreset Selection with Prioritized Multiple Objectives

TRIAGE: Characterizing and auditing training data for improved
  regression

Does "Deep Learning on a Data Diet" reproduce? Overall yes, but GraNd at
  Initialization does not

Advancing Deep Active Learning & Data Subset Selection: Unifying
  Principles with Information-Theory Intuitions


Attention-based Deep Multiple Instance Learning

Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classication

Prediction of heart transplant rejection from routine pathology slides with self-supervised deep learning

Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer


Noise2Noise: Learning Image Restoration without Clean Data - Official TensorFlow implementation of the ICML 2018 paper

Noisier2Noise: Learning to Denoise from Unpaired Noisy Data

A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy Images

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era

Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography


Machine learning-based integrative analysis develops an immune-derived lncRNA signature for improving clinical outcomes in colorectal cancer

Bioinformatics identification of a T‐cell‐related signature for predicting prognosis and drug sensitivity in hepatocellular carcinoma

A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning

Machine learning developed a programmed cell death signature for predicting prognosis and immunotherapy benefits in lung adenocarcinoma


Learned Primal-Dual Reconstruction

Learned Primal-Dual Reconstruction

Learned convex regularizers for inverse problems

Learning to solve inverse problems using Wasserstein loss

End-to-end reconstruction meets data-driven regularization for inverse problems


Mastering Atari with Discrete World Models

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning

Reinforcement Learning with Action-Free Pre-Training from Videos

TransDreamer: Reinforcement Learning with Transformer World Models

DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations

Structured World Models from Human Videos

Exploration and preference satisfaction trade-off in reward-free learning

Curiosity-Driven Exploration via Latent Bayesian Surprise

DreamingV2: Reinforcement Learning with Discrete World Models without Reconstruction

Touch-based Curiosity for Sparse-Reward Tasks


MagNet: a Two-Pronged Defense against Adversarial Examples

MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples

Better the Devil you Know: An Analysis of Evasion Attacks using
  Out-of-Distribution Adversarial Examples

On the Limitation of MagNet Defense Against L1-Based Adversarial Examples

Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples

Conference on Data and Application Security and Privacy

Liuer Mihou: A Practical Framework for Generating and Evaluating
  Grey-box Adversarial Attacks against NIDS

ON THE UTILITY OF CONDITIONAL GENERATION BASED MUTUAL INFORMATION FOR CHARACTERIZING ADVERSARIAL SUBSPACES


[ICCV2023 Oral] NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion

From big to small: Multi-scale local planar guidance for monocular depth estimation


A continually expanding collection of cancer genomics notes and data

GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

Inferring tumour purity and stromal and immune cell admixture from expression data

UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses

Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients

GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis

Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells

The prognostic landscape of genes and infiltrating immune cells across human cancers

Next-generation characterization of the Cancer Cell Line Encyclopedia

Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

Comprehensive Characterization of Cancer Driver Genes and Mutations


SIGN: Scalable Inception Graph Network

SIGN: Scalable Inception Graph Neural Networks

Node Dependent Local Smoothing for Scalable Graph Learning

Convolutional Neural Networks on Graphs with Chebyshev Approximation,
  Revisited

IGLU: Efficient GCN Training via Lazy Updates

A Comprehensive Survey on Graph Summarization with Graph Neural Networks


Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)

Feature Selection using Stochastic Gates

A Theoretical Analysis on Independence-driven Importance Weighting for
  Covariate-shift Generalization

Where to Pay Attention in Sparse Training for Feature Selection?

Composite Feature Selection using Deep Ensembles

Supervised Feature Selection with Neuron Evolution in Sparse Neural
  Networks

Effective Neural Network L_0 Regularization With BinMask


scDeepCluster for Single Cell RNA-seq data

Deep learning tackles single-cell analysis A survey of deep learning for
  scRNA-seq analysis

Deep Learning in Single-Cell Analysis


Pytorch implementation of preconditioned stochastic gradient descent (affine group preconditioner, low-rank approximation preconditioner and more)

New Insights and Perspectives on the Natural Gradient Method

Preconditioned Stochastic Gradient Descent

IEEE transactions on neural networks and learning systems

Preconditioner on Matrix Lie Group for SGD

Black Box Lie Group Preconditioners for SGD

Curvature-Informed SGD via General Purpose Lie-Group Preconditioners


PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.

Conservative Q-Learning for Offline Reinforcement Learning

Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient

Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement
  Learning from Suboptimal Demonstrations


A collection of labeled car driving datasets

PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms

Real-time End-to-End Federated Learning: An Automotive Case Study

Distilling and Transferring Knowledge via cGAN-generated Samples for
  Image Classification and Regression

Road Context-aware Intrusion Detection System for Autonomous Cars

Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images.

Label Encoding for Regression Networks


Implementation of deep learning models for time series in PyTorch.

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Adversarial Attacks on Probabilistic Autoregressive Forecasting Models

On the impact of deep learning-based time-series forecasts on multistage stochastic programming policies

Taming the Long Tail of Deep Probabilistic Forecasting

MECATS: Mixture-of-Experts for Quantile Forecasts of Aggregated Time Series


AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

FLM-101B: An Open LLM and How to Train It with $100K Budget

LawBench: Benchmarking Legal Knowledge of Large Language Models

Orion-14B: Open-source Multilingual Large Language Models


Deep Learning to Improve Breast Cancer Detection on Screening Mammography

Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network

Breast Cancer Dataset, Classification and Detection Using Deep Learning

Beyond Fine-tuning: Classifying High Resolution Mammograms using
  Function-Preserving Transformations

Multi-Task Fusion for Improving Mammography Screening Data Classification

Meta-repository of screening mammography classifiers

A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

An XAI Approach to Deep Learning Models in the Detection of DCIS


Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)

Conflict-Averse Gradient Descent for Multi-task Learning

Value Function Decomposition for Iterative Design of Reinforcement
  Learning Agents

Challenging Common Paradigms in Multi-Task Learning


Open source code for ACL 2020 Paper "Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog"

Global-to-local Memory Pointer Networks for Task-Oriented Dialogue

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems

Intention Reasoning Network for Multi-Domain End-to-end Task-Oriented Dialogue

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing


MixMatch: A Holistic Approach to Semi-Supervised Learning

ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring

Interpolation-Based Contrastive Learning for Few-Label Semi-Supervised Learning

Enhancing MR Image Segmentation with Realistic Adversarial Data
  Augmentation

Training on Test Data with Bayesian Adaptation for Covariate Shift

Fix-A-Step: Semi-supervised Learning from Uncurated Unlabeled Data

Navigating the Pitfalls of Active Learning Evaluation: A Systematic
  Framework for Meaningful Performance Assessment


SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY

SNIP: Single-shot Network Pruning based on Connection Sensitivity

Pruning Neural Networks at Initialization: Why are We Missing the Mark?

FreezeNet: Full Performance by Reduced Storage Costs

End-to-End Supermask Pruning: Learning to Prune Image Captioning Models


KnowBert -- Knowledge Enhanced Contextual Word Representations

TuckER: Tensor Factorization for Knowledge Graph Completion

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT

Neural Entity Linking: A Survey of Models Based on Deep Learning

Pre-train or Annotate? Domain Adaptation with a Constrained Budget

Metadata Shaping: A Simple Approach for Knowledge-Enhanced Language Models

Findings of the Association for Computational Linguistics: ACL 2022


Data and analysis for the BuzzFeed News article, "Hyperpartisan Facebook Pages Are Publishing False And Misleading Information At An Alarming Rate."

A Stylometric Inquiry into Hyperpartisan and Fake News

Hong Kong Protests: Using Natural Language Processing for Fake News Detection on Twitter

IFIP advances in information and communication technology

Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Disinformation Detection: A review of linguistic feature selection and classification models in news veracity assessments.


Convolutional Neural Tangent Kernel

On Exact Computation with an Infinitely Wide Neural Net

Global Convergence and Induced Kernels of Gradient-Based Meta-Learning with Neural Nets.

Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets


implementation of STGCN for traffic prediction in IJCAI2018

Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions

IEEE transactions on intelligent transportation systems

A Comprehensive Survey on Traffic Prediction.

Graph Neural Networks for Intelligent Transportation Systems: A Survey


Semantic Entity Retrieval Toolkit

Learning Latent Vector Spaces for Product Search

International Conference on Information and Knowledge Management

Neural information retrieval: at the end of the early years

Towards Question-based Recommender Systems

PROCEEDINGS OF THE 43RD INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '20)

Unsupervised, Efficient and Semantic Expertise Retrieval

Semantic Entity Retrieval Toolkit

Structural Regularities in Text-based Entity Vector Spaces

International Conference on the Theory of Information Retrieval

Getting Started with Neural Models for Semantic Matching in Web Search

Remedies against the Vocabulary Gap in Information Retrieval


Image Editing Anything

A Comprehensive Survey on Segment Anything Model for Vision and Beyond

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets
  Prompt Engineering

Segment Anything in Non-Euclidean Domains: Challenges and Opportunities


The code for ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples (CVPR2019)

Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples

Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework


Re-entrancy attack patterns from our paper "Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks"

Smart Contract Vulnerabilities: Vulnerable Does Not Imply Exploited

RA: Hunting for Re-Entrancy Attacks in Ethereum Smart Contracts via Static Analysis

International Congress on Blockchain and Applications

Empirical Review of Smart Contract and DeFi Security: Vulnerability
  Detection and Automated Repair


[AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients

Communication-Efficient Learning of Deep Networks from Decentralized Data

Tackling Data Heterogeneity in Federated Learning with Class Prototypes

FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks


MOS score prediction by fine-tuned wav2vec2.0 model

HiFi++: a Unified Framework for Bandwidth Extension and Speech
  Enhancement

Analysing Diffusion-based Generative Approaches versus Discriminative
  Approaches for Speech Restoration

Diffusion Posterior Sampling for Informed Single-Channel Dereverberation

UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Model


:speech_balloon: Sequence to Sequence from Scratch Using Pytorch

Neural Machine Translation by Jointly Learning to Align and Translate

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Sequence to Sequence Learning with Neural Networks


About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018)

Multivariate Time Series Anomaly Detection: Fancy Algorithms and Flawed
  Evaluation Methodology


How Powerful are Graph Neural Networks?

A Comprehensive Survey on Graph Neural Networks

How Powerful are Graph Neural Networks?

Deep Learning on Graphs: A Survey

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning

On the equivalence between graph isomorphism testing and function approximation with GNNs

Random Features Strengthen Graph Neural Networks

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs

K-Core Based Temporal Graph Convolutional Network for Dynamic Graphs

IEEE transactions on knowledge and data engineering

Going Deeper into Permutation-Sensitive Graph Neural Networks


Experiments for the Neural Autoregressive Flows paper

Neural Autoregressive Flows

A Comprehensive Survey of AI-Generated Content (AIGC): A History of
  Generative AI from GAN to ChatGPT

Leveraging exploration in off-policy algorithms via normalizing flows

Variation Network: Learning High-level Attributes for Controlled Input
  Manipulation


repository for Universal Domain Adaptation through Self-supervision

Universal Domain Adaptation through Self Supervision

Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density

Domain Adaptation under Open Set Label Shift

Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation

Universal Domain Adaptation from Foundation Models: A Baseline Study

Synthetic Source Universal Domain Adaptation through Contrastive Learning


Deep Learning tools for brain medical images

Brain MRI Analysis for Alzheimer’s Disease Diagnosis Using CNN-Based Feature Extraction and Machine Learning

A collaborative resource platform for non-human primate neuroimaging

A Multi-Stream Convolutional Neural Network for Classification of Progressive MCI in Alzheimer’s Disease Using Structural MRI Images

IEEE journal of biomedical and health informatics

Learning to synthesise the ageing brain without longitudinal data

Multi-scale Neural ODEs for 3D Medical Image Registration

Classification of Alzheimer's Disease Using the Convolutional Neural
  Network (CNN) with Transfer Learning and Weighted Loss

NEURO-DRAM: a 3D recurrent visual attention model for interpretable neuroimaging classification

A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer’s Disease

Adversarial Counterfactual Augmentation: Application in Alzheimer's
  Disease Classification

A “Seed-and-Soil” Radiomics Model Predicts Brain Metastasis Development in Lung Cancer: Implications for Risk-Stratified Prophylactic Cranial Irradiation


Binarize convolutional neural networks using pytorch :fire:

XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources

International Conference on Computer Vision

XNOR-Net++: Improved Binary Neural Networks

Improved training of binary networks for human pose estimation and image
  recognition

Hierarchical Binary CNNs for Landmark Localization with Limited Resources

IEEE transactions on pattern analysis and machine intelligence


ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring

ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring

Clustering by Maximizing Mutual Information Across Views

Reliable Label Bootstrapping for Semi-Supervised Learning


A clean and readable Pytorch implementation of CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

AI for radiographic COVID-19 detection selects shortcuts over signal

medRxiv : the preprint server for health sciences

Mutually Improved Endoscopic Image Synthesis and Landmark Detection in Unpaired Image-to-Image Translation

Domain Adaptation via CycleGAN for Retina Segmentation in Optical Coherence Tomography.


Cross-platform software to draw phylogenetic trees

Loss of key endosymbiont genes may facilitate early host control of the chromatophore in Paulinella

High resolution species assignment of Anopheles mosquitoes using k-mer distances on targeted sequences

Niche and ecosystem preference of earliest diverging fungi in soils


Offical implementation of "Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series" (ICLR 2022)

Is It Worth It? Comparing Six Deep and Classical Methods for Unsupervised Anomaly Detection in Time Series

A Causal Approach to Detecting Multivariate Time-series Anomalies and
  Root Causes


A project with topic model implementations

On a Topic Model for Sentences

Topical Coherence in LDA-based Models through Induced Segmentation

PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 1

Machine learning for learner English

International journal of learner corpus research

Modeling topic dependencies in semantically coherent text spans with copulas

International Conference on Computational Linguistics

Lexical Bias In Essay Level Prediction


Quick Draw Irregular Mask Dataset

Image Inpainting for Irregular Holes Using Partial Convolutions

Efficient texture-aware multi-GAN for image inpainting

Pixel-wise Dense Detector for Image Inpainting

A Benchmark for Inpainting of Clothing Images with Irregular Holes

Texture-aware Multi-resolution Image Inpainting.


Caffe: a fast open framework for deep learning.

Domain Adaptation for Visual Applications: A Comprehensive Survey

Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild

Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment


TRIQ implementation

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Transformer for Image Quality Assessment

Attention integrated hierarchical networks for no-reference image quality assessment

Journal of visual communication and image representation


Learning to Decompose and Disentangle Representations for Video Prediction, NIPS 2018

Structured Object-Aware Physics Prediction for Video Modeling and Planning

Deep Learning for Vision-based Prediction: A Survey

Disentangling Multiple Features in Video Sequences using Gaussian Processes in Variational Autoencoders

ARMA Nets: Expanding Receptive Field for Dense Prediction


[ACM TOMM 2023] - Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features

Effective conditioned and composed image retrieval combining CLIP-based features

Conditioned and composed image retrieval combining and partially fine-tuning CLIP-based features

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Bi-directional Training for Composed Image Retrieval via Text Prompt
  Learning


3D Boolean / CSG Library

Fast Tetrahedral Meshing in the Wild

Improving model-based fNIRS analysis using mesh-based anatomical and light-transport models

As-exact-as-possible repair of unprintable STL files

Dual Graded Lattice Structures: Generation Framework and Mechanical Properties Characterization

Fast and high-quality tetrahedral mesh generation from neuroanatomical scans

Interactive and Robust Mesh Booleans

Designing modular 3D printed reinforcement of wound composite hollow beams with semidefinite programming


Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".

A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research

ACM transactions on office information systems

Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering

Self-Attentive Neural Collaborative Filtering

COMET: Convolutional Dimension Interaction for Collaborative Filtering


Multi-Objective Molecule Generation using Interpretable Substructures (ICML 2020)

MARS: Markov Molecular Sampling for Multi-objective Drug Discovery

Graph-based Molecular Representation Learning

How Much Space Has Been Explored? Measuring the Chemical Space Covered
  by Databases and Machine-Generated Molecules


CSV spreadsheets and other material for AI accelerator survey papers

1.1 Computing's energy problem (and what we can do about it)

International Solid-State Circuits Conference

The End of Moore's Law: A New Beginning for Information Technology

A new golden age for computer architecture

There’s plenty of room at the Top: What will drive computer performance after Moore’s law?

Domain-specific hardware accelerators

Survey and Benchmarking of Machine Learning Accelerators

IEEE High Performance Extreme Computing Conference

Survey of Machine Learning Accelerators

AI Accelerator Survey and Trends

The decline of computers as a general purpose technology

AI and ML Accelerator Survey and Trends


Corpus of Russian news articles collected from Lenta.Ru

Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named Entity Recognition

Argumentation, Critical Reasoning, and Problem Solving

Advances of Transformer-Based Models for News Headline Generation

Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian

Tracing cultural diachronic semantic shifts in Russian using word embeddings: test sets and baselines

HeadlineCause: A Dataset of News Headlines for Detecting Causalities

Russian Natural Language Generation: Creation of a Language Modelling Dataset and Evaluation with Modern Neural Architectures


Weighted Principal Component Analysis (PCA) in Python

Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences

A large sub-Neptune transiting the thick-disk M4 V TOI-2406

FIESTA II. Disentangling Stellar and Instrumental Variability from Exoplanetary Doppler Shifts in the Fourier Domain

Development of the SPECULOOS exoplanet search project

Ground-based and Airborne Telescopes VIII

: a data-driven approach to correct for systematics in
  RV data – Application to SPIRou data of the planet-hosting M dwarf GJ 251


Code for ICLR 2023 paper (Oral) — Towards Stable Test-Time Adaptation in Dynamic Wild World

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition


RAVEN: A Dataset for Relational and Analogical Visual rEasoNing

Few-shot Visual Reasoning with Meta-analogical Contrastive Learning


Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Learning both Weights and Connections for Efficient Neural Networks

EIE: Efficient Inference Engine on Compressed Deep Neural Network


This repository contains the official implementation of GhostFaceNets, State-Of-The-Art lightweight face recognition models.

On the Variance of the Adaptive Learning Rate and Beyond

Lookahead Optimizer: k steps forward, 1 step back

Gradient Centralization: A New Optimization Technique for Deep Neural Networks

GhostFaceNets: Lightweight Face Recognition Model From Cheap Operations


Calibration of Convolutional Neural Networks

Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks

Better Uncertainty Calibration via Proper Scores for Classification and
  Beyond

Post-hoc Calibration of Neural Networks by g-Layers

Introspective Learning : A Two-Stage Approach for Inference in Neural
  Networks


[NeurIPS 2022] Official pytorch implementation of EpiGRAF

EpiGRAF: Rethinking training of 3D GANs

DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis

BallGAN: 3D-aware Image Synthesis with a Spherical Background


Deep Learning on Graphs: A Survey

Graph Convolutional Matrix Completion

Graph Learning based Recommender Systems: A Review

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation


Implementation of our papers Joint entity recognition and relation extraction as a multi-head selection problem (Expert Syst. Appl, 2018) and Adversarial training for multi-context joint entity and relation extraction (EMNLP, 2018).

Neural Metric Learning for Fast End-to-End Relation Extraction

Putting Them under Microscope: A Fine-Grained Approach for Detecting
  Redundant Test Cases in Natural Language


Pytorch implementation of Compressive Transformers, from Deepmind

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Compressive Transformers for Long-Range Sequence Modelling

GLU Variants Improve Transformer

Stabilizing Transformers for Reinforcement Learning

A bio-inspired bistable recurrent cell allows for long-lasting memory


Code for Shifted Diffusion for Text-to-image Generation (CVPR 2023)

Hierarchical Text-Conditional Image Generation with CLIP Latents

Towards Language-Free Training for Text-to-Image Generation


Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"

Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One

Controversial stimuli: Pitting neural networks against each other as models of human cognition

No MCMC for me: Amortized sampling for fast and stable training of energy-based models

Scalable Bayesian Inverse Reinforcement Learning

Strictly Batch Imitation Learning by Energy-based Distribution Matching

Hybrid Discriminative-Generative Training via Contrastive Learning

Towards Understanding the Generative Capability of Adversarially Robust Classifiers

JEM++: Improved Techniques for Training JEM

Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling

An Algorithm for Out-Of-Distribution Attack to Neural Network Encoder


Public repository for the CVPR 2020 paper AvatarMe and the TPAMI 2021 AvatarMe++

Deep Learning for Deepfakes Creation and Detection: A Survey

AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"

AvatarMe++: Facial Shape and BRDF Inference with Photorealistic Rendering-Aware GANs

A Review of Image Processing Techniques for Deepfakes


Pytroch implementation of MolGAN: An implicit generative model for small molecular graphs (https://arxiv.org/abs/1805.11973)

Accurate Learning of Graph Representations with Graph Multiset Pooling

Edge Representation Learning with Hypergraphs


speech self-supervised representations

ContentVec: An Improved Self-Supervised Speech Representation by
  Disentangling Speakers


Framework for evaluating Graph Neural Network models on semi-supervised node classification task

Deep Learning on Graphs: A Survey

Pitfalls of Graph Neural Network Evaluation

Graph Contrastive Learning with Adaptive Augmentation

Graph Random Neural Network for Semi-Supervised Learning on Graphs

Large-Scale Representation Learning on Graphs via Bootstrapping

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning

Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study

Graph Communal Contrastive Learning

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining


Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

Neural Machine Translation by Jointly Learning to Align and Translate

Sequence to Sequence Learning with Neural Networks

A Deep Reinforced Model for Abstractive Summarization

Long Short-Term Memory-Networks for Machine Reading

A Survey on Text Classification: From Shallow to Deep Learning

RRA: Recurrent Residual Attention for Sequence Learning


Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Rethinking the Pruning Criteria for Convolutional Neural Network

Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks

Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck

TREND: Truncated Generalized Normal Density Estimation of Inception
  Embeddings for GAN Evaluation

Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees

Learning Distributions via Monte-Carlo Marginalization

Adapt then Unlearn: Exploiting Parameter Space Semantics for Unlearning
  in Generative Adversarial Networks


Code for the paper Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models (ICLR 2022 Outstanding Paper Award)

A Comprehensive Survey of AI-Generated Content (AIGC): A History of
  Generative AI from GAN to ChatGPT

Fast Sampling of Diffusion Models with Exponential Integrator


[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation

Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions

Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation

VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting

VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions

Consistency Regularization for Domain Adaptation


[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

EdiBERT, a generative model for image editing

Conditional Image Generation by Conditioning Variational Auto-Encoders

Perceptual Artifacts Localization for Image Synthesis Tasks

Comparison of CoModGANs, LaMa and GLIDE for Art Inpainting Completing M.C Escher’s Print Gallery


A simplified PyTorch implementation of Siamese networks for tracking: SiamFC, SiamRPN, SiamRPN++, SiamVGG, SiamDW, SiamRPN-VGG.

Fully-Convolutional Siamese Networks for Object Tracking

SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks

Deeper and Wider Siamese Networks for Real-Time Visual Tracking

SiamVGG: Visual Tracking using Deeper Siamese Networks


implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)

2nd Place Solution for Waymo Open Dataset Challenge - Real-time 2D Object Detection

Perceptual Pat: A Virtual Human Visual System for Iterative Visualization Design


Automatically exported from code.google.com/p/berkeleyparser

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts

Chinese Zero Pronoun Resolution with Deep Memory Network

Empirical Methods in Natural Language Processing

A Top-Down Neural Architecture towards Text-Level Parsing of Discourse
  Rhetorical Structure

Generic Partition Refinement and Weighted Tree Automata

SCTB: A Chinese Treebank in Scientific Domain

Language Independent Dependency to Constituent Tree Conversion

Supervised Syntax-based Alignment between English Sentences and Abstract Meaning Representation Graphs

Automatic Topological Field Identification in (Historical) German Texts

DynamicPower at SemEval-2016 Task 8: Processing syntactic parse trees with a Dynamic Semantics core

North American Chapter of the Association for Computational Linguistics

Cross-language Projection of Dependency Trees with Constrained Partial Parsing for Tree-to-Tree Machine Translation

Proceedings of the First Conference on Machine Translation: Volume 1,
          Research Papers


The official repository of the paper: COLD: A Benchmark for Chinese Offensive Language Detection

Enhancing Psychological Counseling with Large Language Model: A
  Multifaceted Decision-Support System for Non-Professionals


Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Matching neural paths: transfer from recognition to correspondence search


Granger causality discovery for neural networks.

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

Neural Granger Causality

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality

Interpretable Models for Granger Causality Using Self-explaining Neural Networks

Neural graphical modelling in continuous-time: consistency guarantees
  and algorithms

Cardinality-Regularized Hawkes-Granger Model

CUTS: Neural Causal Discovery from Irregular Time-Series Data


IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition

A Graph-Related High-Order Neural Network Architecture via Feature Aggregation Enhancement for Identification Application of Diseases and Pests

Computational intelligence and neuroscience

IoT-Enabled Pest Identification and Classification with New Meta-Heuristic-Based Deep Learning Framework

Detection of Rice Pests Based on Self-Attention Mechanism and Multi-Scale Feature Fusion

Pests Identification of IP102 by YOLOv5 Embedded with the Novel Lightweight Module

A YOLOv7 incorporating the Adan optimizer based corn pests identification method


Code and resources for "FC4 : Fully Convolutional Color Constancy with Confidence-weighted Pooling" (CVPR 2017)

FC^4: Fully Convolutional Color Constancy with Confidence-Weighted Pooling

CNN-Based Illumination Estimation with Semantic Information

Self-adaptive Single and Multi-illuminant Estimation Framework based on Deep Learning


Pre-training without Natural Images (ACCV 2020 Best Paper Honorable Mention Award)

Pre-training without Natural Images

Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models

Can Vision Transformers Learn without Natural Images?

Predicting Atlantic Multidecadal Variability


This is a language detection library implemented in plain Java. (aliases: language identification, language guessing)

We Value Your Privacy ... Now Take Some Cookies: Measuring the GDPR's Impact on Web Privacy

Proceedings 2019 Network and Distributed System Security Symposium

Automatic Language Identification in Texts: A Survey

Collective Emotions and Social Resilience in the Digital Traces After a Terrorist Attack

Towards a Question Answering System over the Semantic Web

TwiSty: A Multilingual Twitter Stylometry Corpus for Gender and Personality Profiling

Zenodo (CERN European Organization for Nuclear Research)

One-To-Many Multilingual End-to-end Speech Translation

WikiBERT models: deep transfer learning for many languages

Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages

EstBERT: A Pretrained Language-Specific BERT for Estonian

Are You Charlie or Ahmed? Cultural Pluralism in Charlie Hebdo Response on Twitter


Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks

Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-Resolution

Studying the Effects of Self-Attention for Medical Image Analysis

Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism

Class Activation Map Generation by Representative Class Selection and Multi-Layer Feature Fusion.

Class Activation Map generation by Multiple Level Class Grouping and Orthogonal Constraint


Publication-quality sequence logos in R

CRISPR-Cas9 cytidine and adenosine base editing of splice-sites mediates highly-efficient disruption of proteins in primary and immortalized cells

Profiling Thermus thermophilus Argonaute Guide DNA Sequence Preferences by Functional Screening

Helicobacter pylori Chronic Infection Selects for Effective Colonizers of Metaplastic Glands

Maternally-inherited anti-sense piRNAs antagonize transposon expression in teleost embryos

mRNA vaccination boosts S-specific T cell memory and promotes expansion of CD45RAint TEMRA-like CD8+ T cells in COVID-19 recovered individuals


Hierarchy-Aware Global Model for Hierarchical Text Classification

Meeting of the Association for Computational Linguistics

Hierarchical Interdisciplinary Topic Detection Model for Research Proposal Classification

Exploring Label Hierarchy in a Generative Way for Hierarchical Text Classification

Interdisciplinary Fairness in Imbalanced Research Proposal Topic
  Inference: A Hierarchical Transformer-based Method with Selective
  Interpolation


Repository to accompany RSS 2018 paper on dexterous hand manipulation

Sample-efficient Cross-Entropy Method for Real-time Planning

Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning

Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Dense and Sparse Reward Environments

Human-in-the-Loop Methods for Data-Driven and Reinforcement Learning Systems.


Webshell && Backdoor Collection

Mitigating Webshell Attacks through Machine Learning Techniques

PBDT: Python Backdoor Detection Model Based on Combined Features

WTA: A Static Taint Analysis Framework for PHP Webshell

BERT-Embedding-Based JSP Webshell Detection on Bytecode Level Using XGBoost


Modern HTTP benchmarking tool

A Fog Computing Based Cyber-Physical System for the Automation of Pipe-Related Tasks in the Industry 4.0 Shipyard

Understanding Open Source Serverless Platforms: Design Considerations and Performance

PACStack: an Authenticated Call Stack

Metaviz: interactive statistical and visual analysis of metagenomic data

An optimizing compiler for a purely functional web-application language

Methodologies for Quantifying (Re-)randomization Security and Timing under JIT-ROP

Analyzing Open-Source Serverless Platforms: Characteristics and Performance

Software Engineering and Knowledge Engineering

Dissecting Service Mesh Overheads

SensorHub: Multimodal Sensing in Real-Life Enables Home-Based Studies

Cheetah: A High-Speed Programmable Load-Balancer Framework With Guaranteed Per-Connection-Consistency


Sparse Subspace Clustering: Algorithm, Theory, and Applications

Deep Subspace Clustering Networks

Self-Supervised Deep Subspace Clustering for Hyperspectral Images With Adaptive Self-Expressive Coefficient Matrix Initialization

IEEE journal of selected topics in applied earth observations and remote sensing

Beyond Linear Subspace Clustering: A Comparative Study of Nonlinear Manifold Clustering Algorithms

A Critique of Self-Expressive Deep Subspace Clustering


[CVPR 2022] Official CoTTA Code for our paper Continual Test-Time Domain Adaptation

Continual Test-Time Domain Adaptation

NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation

EcoTTA: Memory-Efficient Continual Test-time Adaptation via
  Self-distilled Regularization

Robust Test-Time Adaptation in Dynamic Scenarios

DELTA: degradation-free fully test-time adaptation

Towards Open-Set Test-Time Adaptation Utilizing the Wisdom of Crowds in Entropy Minimization

SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

RDumb: A simple approach that questions our progress in continual
  test-time adaptation

Generalized Robust Test-Time Adaptation in Continuous Dynamic Scenarios


Deep Ordinal Regression Network for Monocular Depth Estimation

Towards Real-Time Monocular Depth Estimation for Robotics: A Survey

Deep Multi-view Depth Estimation with Predicted Uncertainty


MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

LSOS: Line-search Second-Order Stochastic optimization methods for
  nonconvex finite sums

Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning

SGDLibrary: A MATLAB library for stochastic gradient descent algorithms


Python library to compute knowledge graph embeddings

A Survey on Knowledge Graphs: Representation, Acquisition, and Applications

IEEE transactions on neural networks and learning systems

Holographic Embeddings of Knowledge Graphs

Representation Learning for Natural Language Processing

The KEEN Universe: An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability

RDFFrames: Knowledge Graph Access for Machine Learning Tools


Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

Learning from Protein Structure with Geometric Vector Perceptrons

ATOM3D: Tasks On Molecules in Three Dimensions

Equivariant Graph Neural Networks for 3D Macromolecular Structure


Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings".

Deep Iterative and Adaptive Learning for Graph Neural Networks

Compact Graph Structure Learning via Mutual Information Compression

GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks


Pytorch implementation of GRU-ODE-Bayes

GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series

A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance.

Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering

Neural Ordinary Differential Equations for Intervention Modeling


Unsupervised Question answering via Cloze Translation

Phrase-Based & Neural Unsupervised Machine Translation

Unsupervised Question Answering by Cloze Translation

Regularization of Distinct Strategies for Unsupervised Question Generation


Bidirectional Learning for Domain Adaptation of Semantic Segmentation

ESL: Entropy-guided Self-supervised Learning for Domain Adaptation in Semantic Segmentation

Robust Deep Learning for Autonomous Driving


Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)

Robustifying Models Against Adversarial Attacks by Langevin Dynamics

Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks

Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions

AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense

Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients


Source codes of our paper in CVPR 2019:  Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection

Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection

MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection

Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models


Unsupervised Statistical Machine Translation

An Effective Approach to Unsupervised Machine Translation

When Does Unsupervised Machine Translation Work

Bilingual Lexicon Induction through Unsupervised Machine Translation

(Almost) Unsupervised Grammatical Error Correction using Synthetic Comparable Corpus

Workshop on Innovative Use of NLP for Building Educational Applications

CUNI Systems for the Unsupervised News Translation Task in WMT 2019

Towards Unsupervised Grammatical Error Correction using Statistical Machine Translation with Synthetic Comparable Corpus.


Repulsion Loss: Detecting Pedestrians in a Crowd. https://arxiv.org/abs/1711.07752

Very Deep Convolutional Networks for Large-Scale Image Recognition

SSD: Single Shot MultiBox Detector


Driver loader for bypassing Windows x64 Driver Signature Enforcement

Acceleration of Statistical Detection of Zero-day Malware in the Memory Dump Using CUDA-enabled GPU Hardware

Microsoft Defender Will Be Defended: MemoryRanger Prevents Blinding
  Windows AV


Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images

Neighbor2Neighbor: A Self-Supervised Framework for Deep Image Denoising

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Unsupervised Image Denoising with Score Function


A neural network model for Chinese named entity recognition

Recurrent Neural Network Grammars

CLUENER2020: Fine-grained Name Entity Recognition for Chinese

Cross-Lingual Named Entity Recognition Using Parallel Corpus: A New
  Approach Using XLM-RoBERTa Alignment

The Named Entity Recognition of Chinese Cybersecurity Using an Active Learning Strategy

Wireless communications and mobile computing

HAPI: A Large-scale Longitudinal Dataset of Commercial ML API
  Predictions

Statistical Dataset Evaluation: Reliability, Difficulty, and Validity


Tensorflow implementation of variational auto-encoder for MNIST

Auto-Encoding Variational Bayes

Reconstruction and Membership Inference Attacks against Generative
  Models

Finding Archetypal Spaces Using Neural Networks


U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

U-Sleep: resilient to AASM guidelines

Quantifying the Impact of Data Characteristics on the Transferability of
  Sleep Stage Scoring Models


High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection, CVPR, 2019

High-Level Semantic Feature Detection: A New Perspective for Pedestrian Detection

Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection

Toward Robust Pedestrian Detection With Data Augmentation


Neural Style Transfer For Chinese Characters

Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis

DG-Font: Deformable Generative Networks for Unsupervised Font Generation

GAN-Based Unpaired Chinese Character Image Translation via Skeleton Transformation and Stroke Rendering

THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

A Unified Framework for Generalizable Style Transfer: Style and Content Separation

Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator

Few-Shot Font Generation by Learning Fine-Grained Local Styles

Handwritten Chinese Font Generation with Collaborative Stroke Refinement

FontGAN: A Unified Generative Framework for Chinese Character Stylization and De-stylization.

DGFont++: Robust Deformable Generative Networks for Unsupervised Font
  Generation


Implements the unsupervised pre-training of convolutional neural networks

Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

Unsupervised Pre-Training of Image Features on Non-Curated Data

Learning Visual Representations with Caption Annotations


pre-trained Language Models

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

FlauBERT: Unsupervised Language Model Pre-training for French

MultiFiT: Efficient Multi-lingual Language Model Fine-tuning


Application for making ENCODE Blacklists

The ENCODE Blacklist: Identification of Problematic Regions of the Genome

Global discovery of lupus genetic risk variant allelic enhancer activity

Control of neurogenic competence in mammalian hypothalamic tanycytes

Histone deacetylase 1 and 2 drive differentiation and fusion of progenitor cells in human placental trophoblasts

Dual histone methyl reader ZCWPW1 facilitates repair of meiotic double strand breaks in male mice

Mapping the evolving landscape of super-enhancers during cell differentiation

Age-related changes in polycomb gene regulation disrupt lineage fidelity in intestinal stem cells

The TH1 cell lineage-determining transcription factor T-bet suppresses TH2 gene expression by redistributing GATA3 away from TH2 genes

SOX9 reprograms endothelial cells by altering the chromatin landscape

Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN


Pronunciation lexicon covering both English and Chinese languages for Automatic Speech Recognition.

WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech
  Recognition

Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec
  Language Modeling

VioLA: Unified Codec Language Models for Speech Recognition, Synthesis,
  and Translation


Tools for state of the art Knowledge Base Completion.

Knowledge Graph Embedding for Link Prediction: A Comparative Analysis

Representation Learning for Dynamic Graphs: A Survey

Canonical Tensor Decomposition for Knowledge Base Completion

LibKGE - A knowledge graph embedding library for reproducible research

PROCEEDINGS OF THE 2020 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING: SYSTEM DEMONSTRATIONS

Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations

On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods

Link Prediction Using Multi Part Embeddings


Image registration algorithm. Includes SIFT, SAR-SIFT,PSO-SIFT.

Intensity-based registration of bright-field and second-harmonic generation images of histopathology tissue sections.

An Instance Segmentation Based Framework for Large-Sized High-Resolution Remote Sensing Images Registration


Equivalent Latitude and  polar vortex edge calculation using Nash criteria


A Probabilistic U-Net for segmentation of ambiguous images implemented in PyTorch

A Probabilistic U-Net for Segmentation of Ambiguous Images

Supervised Uncertainty Quantification for Segmentation with Multiple Annotations

Disentangling Human Error from the Ground Truth in Segmentation of Medical Images

Uncertainty quantification in medical image segmentation with normalizing flows

Tensor Networks for Medical Image Classification

Medical Matting: A New Perspective on Medical Segmentation with Uncertainty

Locally orderless tensor networks for classifying two- and three-dimensional medical images

The journal of machine learning for biomedical imaging

Topology-Aware Uncertainty for Image Segmentation

Generalized Probabilistic U-Net for medical image segementation

Operating critical machine learning models in resource constrained
  regimes


Multilingual/multidomain question generation datasets, models, and python library for question generation.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language
  Generation, Translation, and Comprehension

Generative Language Models for Paragraph-Level Question Generation

An Empirical Comparison of LM-based Question and Answer Generation Methods

A Practical Toolkit for Multilingual Question and Answer Generation


automatic video description generation with GPU training

Theano: A Python framework for fast computation of mathematical expressions

Describing Videos by Exploiting Temporal Structure

Delving Deeper into Convolutional Networks for Learning Video Representations

End-to-End Video Captioning

Oracle performance for visual captioning


PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT

Generalization through Memorization: Nearest Neighbor Language Models

Nearest Neighbor Machine Translation

Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models

KNN-LM Does Not Improve Open-ended Text Generation

knn-seq: Efficient, Extensible kNN-MT Framework


Simple implementation of OpenAI CLIP model in PyTorch.

Learning Transferable Visual Models From Natural Language Supervision

Domino: Discovering Systematic Errors with Cross-Modal Embeddings

GSCLIP : A Framework for Explaining Distribution Shifts in Natural
  Language

ENIGMA-51: Towards a Fine-Grained Understanding of Human-Object
  Interactions in Industrial Scenarios


Boltzmann machine learning for Potts models of biological data

Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families

adabmDCA: Adaptive Boltzmann machine learning for biological sequences

Aligning biological sequences by exploiting residue conservation and coevolution


This repository is the official implementation of "DTL: Disentangled Transfer Learning for Visual Recognition", which is accepted by AAAI 2024.

LoRA: Low-Rank Adaptation of Large Language Models

Parameter-Efficient Transfer Learning for NLP

Visual Prompt Tuning