Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data

SpaGE: Spatial Gene Enhancement using scRNA-seq

Computational Approaches and Challenges in Spatial Transcriptomics

基因组蛋白质组与生物信息学报

stDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics


(SIGKDD 2022) Connected Low-Loss Subspace Learning for a Personalization in Federated Learning (https://arxiv.org/abs/2109.07628)

Communication-Efficient Learning of Deep Networks from Decentralized Data

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Connecting Low-Loss Subspace for Personalized Federated Learning

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


SSG-VQA is a Visual Question Answering (VQA) dataset on laparoscopic videos providing diverse, geometrically grounded, unbiased and surgical action-oriented queries generated using scene graphs.

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks

Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos

CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80

Advancing Surgical VQA with Scene Graph Knowledge


Official code for "CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis", ICML 2023

Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space


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


deep learning for math

DeepMath - Deep Sequence Models for Premise Selection

Reinforcement Learning of Theorem Proving

Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling

A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving

Prolog Technology Reinforcement Learning Prover

Learning to Guide a Saturation-Based Theorem Prover

Premise selection with neural networks and distributed representation of features

The Role of Entropy in Guiding a Connection Prover

An Experimental Study of Formula Embeddings for Automated Theorem Proving in First-Order Logic


Pipeline to detect PAVs (presence/absence variations) in genome comparison using whole genome alignment.

A mini foxtail millet with an Arabidopsis-like life cycle as a C4 model system

The Origins and Vulnerabilities of Two Transmissible Cancers in Tasmanian Devils

Telomere-to-telomere and gap-free genome assembly of a susceptible grapevine species (Thompson Seedless) to facilitate grape functional genomics


A false-positive filter for variants called from massively parallel sequencing

Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma

Combination of Flow Cytometry and Functional Imaging for Monitoring of Residual Disease in Myeloma

Multi-region sequencing unveils novel actionable targets and spatial heterogeneity in esophageal squamous cell carcinoma

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

The spatio-temporal evolution of multiple myeloma from baseline to relapse-refractory states

Exome scale map of genetic alterations promoting metastasis in colorectal cancer

The genomic and epigenomic evolutionary history of papillary renal cell carcinomas

ASXL2 regulates hematopoiesis in mice and its deficiency promotes myeloid expansion

Poor overall survival in hyperhaploid multiple myeloma is defined by double-hit bi-allelic inactivation of TP53.

Evolutionary Trajectories and Genomic Divergence in Localized Breast Cancers after Ipsilateral Breast Tumor Recurrence


R package for transfer learning of single-cell RNA-seq denoising

Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review

基因组蛋白质组与生物信息学报

Imputation Methods for scRNA Sequencing Data

An Overview of Algorithms and Associated Applications for Single Cell RNA-Seq Data Imputation


Online Continual Learning through Mutual Information Maximization

International Conference on Machine Learning

Online Prototype Learning for Online Continual Learning

Online Continual Learning via Logit Adjusted Softmax

Orchestrate Latent Expertise: Advancing Online Continual Learning with
  Multi-Level Supervision and Reverse Self-Distillation


Hyperspectral Super-Resolution by Coupled Spectral Unmixing

Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution

Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution With Subpixel Fusion

Self-Dictionary Regression for Hyperspectral Image Super-Resolution

A Multiresolution Details Enhanced Attentive Dual-UNet for Hyperspectral and Multispectral Image Fusion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Hyperspectral Image Super-Resolution Based on Spatial Group Sparsity Regularization Unmixing


Code for Heaton et al (in JABES, 2018)

Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains

Journal of the American Statistical Association

Statistical Deep Learning for Spatial and Spatio-Temporal Data

MuyGPs: Scalable Gaussian Process Hyperparameter Estimation Using Local Cross-Validation

Precision Aggregated Local Models

Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation

Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data

Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization


MUSE: Modularizing Unsupervised Sense Embeddings

Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy


Paper implemention of paper "Blind Image Deconvolution using Deep Generative Priors"

Progressive Growing of GANs for Improved Quality, Stability, and Variation

Blind Image Deconvolution using Pretrained Generative Priors


Genomic Multivariate Analysis Tools

Rapid Epistatic Mixed Model Association Studies by Controlling Multiple Polygenic Effects

Marker density and statistical model designs to increase accuracy of genomic selection for wool traits in Angora rabbits

An Improved Linear Mixed Model for Multivariate Genome-Wide Association Studies


Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images (TIP 2018)

Multi-Exposure Image Fusion Techniques: A Comprehensive Review

Unsupervised Multi-Exposure Image Fusion Breaking Exposure Limits via Contrastive Learning

Proceedings of the AAAI Conference on Artificial Intelligence

Image Fusion via Vision-Language Model

LightFuse: Lightweight CNN based Dual-exposure Fusion

Low-Light Image Enhancement Method for Electric Power Operation Sites Considering Strong Light Suppression


Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022

GSLB: The Graph Structure Learning Benchmark

Combating Bilateral Edge Noise for Robust Link Prediction


Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting

Contrastive Learning Improves Model Robustness Under Label Noise


Figure 1 COVID-19 Chest X-ray Dataset Initiative

COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images

CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images

Dynamic Fusion based Federated Learning for COVID-19 Detection

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

DeepCOVIDExplainer: Explainable COVID-19 Diagnosis Based on Chest X-ray Images

A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19

CovidXrayNet: Optimizing data augmentation and CNN hyperparameters for improved COVID-19 detection from CXR

SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network

Artificial Intelligence applied to chest X-Ray images for the automatic detection of COVID-19. A thoughtful evaluation approach

FLOP: Federated Learning on Medical Datasets using Partial Networks


BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA

Workshop on Biomedical Natural Language Processing

Transferability of Natural Language Inference to Biomedical Question Answering

Leveraging Biomolecule and Natural Language through Multi-Modal
  Learning: A Survey


A python script for finding telomeric repeats (TTAGGG/CCCTAA) in FASTA files

Genomic insights into the host specific adaptation of the Pneumocystis genus

A highly-contiguous genome assembly of the Eurasian spruce bark beetle, Ips typographus, provides insight into a major forest pest

A chromosomal-level reference genome of the widely utilizedCoccidioides posadasiilaboratory strain “Silveira”

New T2T assembly ofCryptosporidium parvumIOWA annotated with reference genome gene identifiers

bioRxiv : the preprint server for biology

A new chromosome-level genome assembly and annotation of Cryptosporidium meleagridis.


Unconstrained Text Detection with Box Supervisionand Dynamic Self-Training

EAST: An Efficient and Accurate Scene Text Detector

Shape Robust Text Detection with Progressive Scale Expansion Network

Polygon-free: Unconstrained Scene Text Detection with Box Annotations


The PyTorch implementation of paper SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL. (NeurIPS 2021)

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training


Author implementation of "Learning Recurrent Span Representations for Extractive Question Answering" (Lee et al. 2016)

Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches.

Learning to Search in Long Documents Using Document Structure

Do Question Answering Modeling Improvements Hold Across Benchmarks?


An implementation of Diffusion-Convolutional Neural Networks in Lasagne and Theano.

Graph Neural Networks: A Review of Methods and Applications

Deep Learning on Graphs: A Survey

Diffusion-Convolutional Neural Networks

Shift Aggregate Extract Networks

State of the Art and Potentialities of Graph-level Learning


Mathematica Markov chain Monte Carlo

The Planetary Mass–Radius Relation and Its Dependence on Orbital Period as Measured by Transit Timing Variations and Radial Velocities

A quintessence dynamical dark energy model from ratio gravity


Computing various measures and generalization bounds on convolutional and fully connected networks

Exploring Generalization in Deep Learning

Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks

Geometry of Optimization and Implicit Regularization in Deep Learning


Code of 'Guided Deep Decoder: Unsupervised Image Pair Fusion'

Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review

Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution With Subpixel Fusion

Unsupervised Hyperspectral and Multispectral Images Fusion Based on the Cycle Consistency


Code to evaluate nonlinear Granger causality using the kernel trick to reduce complexity

Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data

Causal Recurrent Variational Autoencoder for Medical Time Series Generation

Discovering Nonlinear Relations with Minimum Predictive Information Regularization

Machine Learning Incorporated With Causal Analysis for Short-Term Prediction of Sea Ice

The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making

Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learning


Automatically exported from code.google.com/p/prottest3

A neurotransmitter produced by gut bacteria modulates host sensory behaviour

Spliceosomal Prp8 intein at the crossroads of protein and RNA splicing

Photoreceptor Diversification Accompanies the Evolution of Anthozoa

Acquisition of a Novel Sulfur-Oxidizing Symbiont in the Gutless Marine Worm Inanidrilus exumae

Caspases from scleractinian coral show unique regulatory features

RNA-Seq de novo assembly and differential transcriptome analysis of the nematode Ascaridia galli in relation to in vivo exposure to flubendazole

From head to rootlet: comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea: Rhizocephala)

Exploring New Routes for Genetic Resistances to Potyviruses: The Case of the Arabidopsis thaliana Phosphoglycerates Kinases (PGK) Metabolic Enzymes

Morphological and molecular evolution of hadal amphipod’s eggs provides insights into embryogenesis under high hydrostatic pressure

Frontiers in cell and developmental biology

A Horizontally Transferred Plant Fatty Acid Desaturase Gene Steers Whitefly Reproduction


Code for the 2019 TACL Paper "Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples"

Towards a Robust Deep Neural Network in Texts: A Survey

Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering

Interpreting Neural Networks With Nearest Neighbors


Explaining and Harnessing Adversarial Examples

Towards Deep Learning Models Resistant to Adversarial Attacks

Theoretically Principled Trade-off between Robustness and Accuracy

Adversarial Logit Pairing

Adversarial Robustness with Semi-Infinite Constrained Learning

Probabilistically Robust Learning: Balancing Average- and Worst-case Performance

It begins with a boundary: A geometric view on probabilistically robust learning


DARTS: Differentiable Architecture Search

Scalable Bayesian Optimization Using Deep Neural Networks

Scalable Global Optimization via Local Bayesian Optimization

Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS


Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction

Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking

Link Prediction without Graph Neural Networks


[NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective

mixup: Beyond Empirical Risk Minimization

Improved Regularization of Convolutional Neural Networks with Cutout

AutoAugment: Learning Augmentation Policies from Data


Tables of ECS, Effective Radiative Forcing, and Radiative Feedbacks from Zelinka et al., GRL (2020).

Increasing Precipitation Efficiency Amplifies Climate Sensitivity by Enhancing Tropical Circulation Slowdown and Eastern Pacific Warming Pattern


Generative adversarial networks for single-cell RNA-seq imputation

scIGANs: single-cell RNA-seq imputation using generative adversarial networks

scRNA‐seq data analysis method to improve analysis performance

Imputation Methods for scRNA Sequencing Data


MAC: Mining Activity Concepts for Language-based Temporal Localization

TALL: Temporal Activity Localization via Language Query

A Survey on Video Moment Localization


Basic VAE flow using pytorch distributions

Categorical Reparameterization with Gumbel-Softmax

Stochastic Gradient VB and the Variational Auto-Encoder

The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

TensorFlow Distributions


[NeurIPS 2023] Meta-Adapter

Learning to Prompt for Vision-Language Models

CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification

Meta-Adapter: An Online Few-shot Learner for Vision-Language Model


Tensor ring low-rank factors (AAAI 2019)

Dictionary Learning With Low-Rank Coding Coefficients for Tensor Completion

Noisy Tensor Completion via Low-rank Tensor Ring

Randomized algorithms for fast computation of low rank tensor ring model

Machine Learning: Science and Technology

Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization


Active Stereo Without Pattern Projector

Active-Passive SimStereo -- Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods


The database contains a vast set of data on the properties of glass materials.

Designing optical glasses by machine learning coupled with a genetic algorithm

ViscNet: Neural network for predicting the fragility index and the temperature-dependency of viscosity

Predicting and interpreting oxide glass properties by machine learning using large datasets

GlassNet: A multitask deep neural network for predicting many glass properties

Reconstructing Chromatic-Dispersion Relations and Predicting Refractive Indices Using Text Mining and Machine Learning

Journal of chemical information and modeling

Revealing the Compositional Control of Electrical, Mechanical, Optical, and Physical Properties of Inorganic Glasses

Machine learning modeling of the atomic structure and physical properties of alkali and alkaline-earth aluminosilicate glasses and melts

Artificial neural networks for predicting the viscosity of lead-containing glasses


This project aims to provide modular implementation and an easy pipeline of training and evaluation for SOTA semantic segmentation models.

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

Rethinking Atrous Convolution for Semantic Image Segmentation

Attention-guided Chained Context Aggregation for Semantic Segmentation


Personality detection on multiparty dialogue

Automatic Text-based Personality Recognition on Monologues and Multiparty Dialogues Using Attentive Networks and Contextual Embeddings

Text-based automatic personality prediction: a bibliographic review

A Survey of Personality, Persona, and Profile in Conversational Agents and Chatbots


A feasible method for optimization with orthogonality constraints

Riemannian Optimization on the Symplectic Stiefel Manifold

Multipliers Correction Methods for Optimization Problems over the Stiefel Manifold

Error bound and exact penalty method for optimization problems with nonnegative orthogonal constraint

An alternate gradient method for optimization problems with orthogonality constraints

Numerical Algebra, Control and Optimization


This repository contains C++ source code used in several publications in the area of route planning.

Real-time Traffic Assignment Using Engineered Customizable Contraction Hierarchies

ACM Journal of Experimental Algorithmics

Real-Time Traffic Assignment Using Fast Queries in Customizable Contraction Hierarchies.

Efficient Calculation of Microscopic Travel Demand Data with Low Calibration Effort

Advances in Geographic Information Systems

Nearest-Neighbor Queries in Customizable Contraction Hierarchies and Applications


A algebraic word problem dataset, with multiple choice questions annotated with rationales.

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems

Faithful Chain-of-Thought Reasoning

Boosting Language Models Reasoning with Chain-of-Knowledge Prompting

DataComp-LM: In search of the next generation of training sets for
  language models

Strategic Chain-of-Thought: Guiding Accurate Reasoning in LLMs through Strategy Elicitation


Adversarial examples for Seq2Seq model in NLP

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples

Towards a Robust Deep Neural Network in Texts: A Survey

TransFool: An Adversarial Attack against Neural Machine Translation Models


Universal Representations: A Unified Look at Multiple Task and Domain Learning

Universal Representation Learning from Multiple Domains for Few-shot Classification

Knowledge Distillation for Multi-task Learning


Circumventing the defense in "Ensemble Adversarial Training: Attacks and Defenses"

Intriguing properties of neural networks

Towards Deep Learning Models Resistant to Adversarial Attacks

Query-Efficient Black-box Adversarial Examples (superceded)


Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning

Representation Based Complexity Measures for Predicting Generalization in Deep Learning

Predicting Deep Neural Network Generalization with Perturbation Response Curves

Gi and Pal Scores: Deep Neural Network Generalization Statistics


(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"

How Do Vision Transformers Work?

Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness

Machine Learning State-of-the-Art with Uncertainties


Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Adversarial Attack and Defense on Graph Data: A Survey

(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More


PyTorch Package For Quasimetric Learning

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality

On the Learning and Learnability of Quasimetrics

Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning

Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings


Unsupervised Spatially Embedded Deep Representation of Spatial Transcriptomics

Deep Learning in Single-Cell Analysis

GNTD: reconstructing spatial transcriptomes with graph-guided neural tensor decomposition informed by spatial and functional relations


Knowledge-Enriched Distributional Model Inversion Attacks

Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks

Re-thinking Model Inversion Attacks Against Deep Neural Networks

Label-Only Model Inversion Attacks via Knowledge Transfer

Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks


Official code for Interspeech 2023 paper "Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering"

SUPERB: Speech processing Universal PERformance Benchmark

R-Spin: Efficient Speaker and Noise-invariant Representation Learning with Acoustic Pieces


Documentation for every thing, everything documented

MR‐based age‐related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan

Early or Late Gestational Exposure to Maternal Immune Activation Alters Neurodevelopmental Trajectories in Mice: An Integrated Neuroimaging, Behavioral, and Transcriptional Study

Investigating the "two-hit hypothesis": effects of prenatal maternal immune activation and adolescent cannabis use on neurodevelopment in mice

Brain Areas Critical for Picture Naming: A Systematic Review and Meta-Analysis of Lesion-Symptom Mapping Studies

Neurobiology of language (Cambridge, Mass.)

Deformation-based shape analysis of the hippocampus in the semantic variant of primary progressive aphasia and Alzheimer’s disease

Morphologic alterations of the fear circuitry: the role of sex hormones and oral contraceptives

Variation in subcortical anatomy: relating interspecies differences, heritability, and brain-behavior relationships

Hippocampal subfield associations with memory depend on stimulus modality and retrieval mode


Collection of scripts for bacterial genomics

Molecular Keys to the Janthinobacterium and Duganella spp. Interaction with the Plant Pathogen Fusarium graminearum

Plant Growth-Promoting Activity of Pseudomonas aeruginosa FG106 and Its Ability to Act as a Biocontrol Agent against Potato, Tomato and Taro Pathogens

Ancestral Absence of Electron Transport Chains in Patescibacteria and DPANN

Genome-Centric Analysis of a Thermophilic and Cellulolytic Bacterial Consortium Derived from Composting

Genome-Based Identification of Active Prophage Regions by Next Generation Sequencing in Bacillus licheniformis DSM13

Genus-wide comparison of Pseudovibrio bacterial genomes reveal diverse adaptations to different marine invertebrate hosts

Propionibacterium avidum as an Etiological Agent of Prosthetic Hip Joint Infection

Genomic and Physiological Properties of a Facultative Methane-Oxidizing Bacterial Strain of Methylocystis sp. from a Wetland

Life at Home and on the Roam: Genomic Adaptions Reflect the Dual Lifestyle of an Intracellular, Facultative Symbiont

Complete genome sequence of the nematicidal Bacillus thuringiensis MYBT18247


Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles

CiteBench: A benchmark for Scientific Citation Text Generation

SKT5SciSumm -- Revisiting Extractive-Generative Approach for Multi-Document Scientific Summarization


Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.

Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation

Efficient and Transferable Adversarial Examples from Bayesian Neural Networks


Code base for "G-Transformer for Document-level Machine Translation"

Contextualized Rewriting for Text Summarization

Exploring Paracrawl for Document-level Neural Machine Translation

Lexical Translation Inconsistency-Aware Document-Level Translation Repair

Findings of the Association for Computational Linguistics: ACL 2023

Modeling Consistency Preference via Lexical Chains for Document-level Neural Machine Translation

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing


Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts

Meeting of the Association for Computational Linguistics

Re-evaluating Evaluation in Text Summarization

Evaluating Question Answering Evaluation

Empirical Methods in Natural Language Processing

Enhancing and Evaluating the Grammatical Framework Approach to Logic-to-Text Generation

Zenodo (CERN European Organization for Nuclear Research)


The code repo contains multiple code reproduction processes of various SOTA deep learning algorithms

Attention Is All You Need

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

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Off-Policy Deep Reinforcement Learning without Exploration

Distributed Distributional Deterministic Policy Gradients

AWAC: Accelerating Online Reinforcement Learning with Offline Datasets


Analytic calibration for differential privacy with Gaussian perturbations

Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising

A Differentially Private Kernel Two-Sample Test

Less is More: Revisiting the Gaussian Mechanism for Differential Privacy


E3Outlier: Effective End-to-end Unsupervised Outlier Detection

Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network

E3 Outlier: A Self-Supervised Framework for Unsupervised Deep Outlier Detection

IEEE transactions on pattern analysis and machine intelligence

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

Latent feature reconstruction for unsupervised anomaly detection


[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

Data-Free Network Quantization With Adversarial Knowledge Distillation

Learning from a Teacher using Unlabeled Data


The dataset and PyTorch Implementation for ACL 2020 paper "MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization".

Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards

Coupling Context Modeling with Zero Pronoun Recovering for Document-Level Natural Language Generation

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


A sentiment analysis platform

Optimizing Word Segmentation for Downstream Task

Joint Optimization of Tokenization and Downstream Model

Word-level Perturbation Considering Word Length and Compositional Subwords

Findings of the Association for Computational Linguistics: ACL 2022


Code for paper Causal Confusion in Imitation Learning

Causal Confusion in Imitation Learning

A Survey on Causal Reinforcement Learning

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

Contextual Reliability: When Different Features Matter in Different Contexts


Decision Transformer: Reinforcement Learning via Sequence Modeling

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction

Offline Reinforcement Learning with Implicit Q-Learning

Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics

AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Mildly Conservative Q-Learning for Offline Reinforcement Learning

Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters


Abbreviation definition dection library trained on PubMed abstracts

Biomedical Entity Representations with Synonym Marginalization

Transferability of Natural Language Inference to Biomedical Question Answering

A Deep Learning-Based System for PharmaCoNER

Better than BERT but Worse than Baseline


SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

TransMix: Attend to Mix for Vision Transformers

SAGE: Saliency-Guided Mixup with Optimal Rearrangements


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


[IJCAI 2023] Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment

Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations

Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning

DiffusionRet: Generative Text-Video Retrieval with Diffusion Model


Official PyTorch Implementation of Learning Affordance Grounding from Exocentric Images, CVPR 2022

Phrase-Based Affordance Detection via Cyclic Bilateral Interaction

Grounded Affordance from Exocentric View


[COLING 2020] EmpDG: Multi-resolution Interactive Empathetic Dialogue Generation

EmpDG: Multiresolution Interactive Empathetic Dialogue Generation

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes

Harnessing the Power of Large Language Models for Empathetic Response Generation: Empirical Investigations and Improvements

Emp-RFT: Empathetic Response Generation via Recognizing Feature Transitions between Utterances

Think Twice: A Human-like Two-stage Conversational Agent for Emotional Response Generation

CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation


A survey of localized sequence rearrangements in human DNA

Robust detection of tandem repeat expansions from long DNA reads

Genome assembly of a Mesoamerican derived variety of lima bean: a foundational cultivar in the Mid-Atlantic USA

DNA Conserved in Diverse Animals Since the Precambrian Controls Genes for Embryonic Development


A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.

Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review

基因组蛋白质组与生物信息学报

siVAE: interpretable deep generative models for single-cell transcriptomes


An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)

Learning Gradient Fields for Molecular Conformation Generation

Graph-based Molecular Representation Learning

3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design


Code release for DeepJudge (S&P'22)

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models

Deep Intellectual Property Protection: A Survey


NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

Symmetric Nonnegative Matrix Factorization for Graph Clustering

SIAM International Conference on Data Mining

Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework

Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons

SymNMF: nonnegative low-rank approximation of a similarity matrix for graph clustering

Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation

Community Detection in Fully-Connected Multi-layer Networks Through Joint Nonnegative Matrix Factorization


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)


Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm

GraphTyper2 enables population-scale genotyping of structural variation using pangenome graphs

Long-molecule scars of backup DNA repair in BRCA1- and BRCA2-deficient cancers

Insights from a genome-wide truth set of tandem repeat variation

bioRxiv : the preprint server for biology

Critical length in long-read resequencing


Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Simple Black-box Adversarial Attacks

Gradient Aligned Attacks via a Few Queries


Supervised Discrete Hashing

Fast Supervised Discrete Hashing and its Analysis

Learning Binary Semantic Embedding for Histology Image Classification and Retrieval


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

ColdNAS: Search to Modulate for User Cold-Start Recommendation

Cross-Domain Meta-Learner for Cold-Start Recommendation

IEEE Transactions on Knowledge and Data Engineering


[CVPR 2023] Robust Test-Time Adaptation in Dynamic Scenarios. https://arxiv.org/abs/2303.13899

SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

Generalized Robust Test-Time Adaptation in Continuous Dynamic Scenarios


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

A low-rank non-convex norm method for multiview graph clustering


Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)

Transformer Hawkes Process

Self-Attentive Hawkes Processes

Transformer Embeddings of Irregularly Spaced Events and Their Participants

HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences

EasyTPP: Towards Open Benchmarking Temporal Point Processes

Prompt-augmented Temporal Point Process for Streaming Event Sequence


Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"

Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)

Streaming Sparse Gaussian Process Approximations

Conditioning Sparse Variational Gaussian Processes for Online Decision-making

Adaptive Sparse Gaussian Process


Ripser: efficient computation of Vietoris–Rips persistence barcodes

A roadmap for the computation of persistent homology

Toroidal topology of population activity in grid cells

Ripser.py: A Lean Persistent Homology Library for Python

Simplicial complexes and complex systems

Learning metrics for persistence-based summaries and applications for graph classification

Connectivity-Optimized Representation Learning via Persistent Homology

Persistent homology of complex networks for dynamic state detection

Computing Minimal Presentations and Bigraded Betti Numbers of 2-Parameter Persistent Homology

Persistent Homology Analysis for Materials Research and Persistent Homology Software: HomCloud

Decoding of neural data using cohomological feature extraction


We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness of OOD detection to various types of adversarial OOD inputs and establishes state-of-the-art performance.

ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining

Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities

READ: Aggregating Reconstruction Error into Out-of-distribution Detection

Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection


Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. Bica, A. M. Alaa, J. Jordon, M. van der Schaar

Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations

Neural Ordinary Differential Equations for Intervention Modeling


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.

Genomic Characteristion of Opportunistic Pathogen Kluyvera Reveals a Novel CTX-M Subgroup

Genomic insights into the evolution, pathogenicity, and extensively drug-resistance of emerging pathogens Kluyvera and Phytobacter

Frontiers in cellular and infection microbiology


A comparative study of fairness-enhancing interventions in machine learning

Understanding artificial intelligence ethics and safety

Bias and Discrimination in AI: A Cross-Disciplinary Perspective

Fairness Testing: A Comprehensive Survey and Analysis of Trends

Educating Software and AI Stakeholders About Algorithmic Fairness, Accountability, Transparency and Ethics

International Journal of Artificial Intelligence in Education

The Right Tool for the Job: Open-Source Auditing Tools in Machine Learning


Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

Maternal-fetal immune responses in pregnant women infected with SARS-CoV-2

Genome-wide bidirectional CRISPR screens identify mucins as host factors modulating SARS-CoV-2 infection

Human Nasal Epithelial Cells Sustain Persistent SARS-CoV-2 Infection In Vitro, despite Eliciting a Prolonged Antiviral Response


KAIST Multispectral Pedestrian Detection Benchmark [CVPR '15]

Unsupervised Image-to-Image Translation Networks

Multispectral Deep Neural Networks for Pedestrian Detection

Learning Cross-Modal Deep Representations for Robust Pedestrian Detection

Improving RGB-Infrared Object Detection by Reducing Cross-Modality Redundancy

Robust Pedestrian Detection Based on Multi-Spectral Image Fusion and Convolutional Neural Networks

Dual-YOLO Architecture from Infrared and Visible Images for Object Detection

Infrared Image Caption Based on Object-Oriented Attention

Pedestrian Detection in Low-Light Conditions: A Comprehensive Survey


DenseNet Implementation in Keras with ImageNet Pretrained Models

Densely Connected Convolutional Networks

Mitigating dataset harms requires stewardship: Lessons from 1000 papers

Deep Learning Predicts Overall Survival of Patients With Unresectable Hepatocellular Carcinoma Treated by Transarterial Chemoembolization Plus Sorafenib


Self-Attentive Hawkes Process

Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes

ACM Transactions on Intelligent Systems and Technology

Continuous-time convolutions model of event sequences


Single-cell and spatial analysis reveal interaction of FAP+ fibroblasts and SPP1+ macrophages in colorectal cancer

scCODA is a Bayesian model for compositional single-cell data analysis

Extracellular vesicles produced by the human commensal gut bacterium Bacteroides thetaiotaomicron affect host immune pathways in a cell-type specific manner that are altered in inflammatory bowel disease


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


Tool for drawing diagrams on a grid, combining grids of SVGs into a big SVG figure

Who witnesses The Witness? Finding witnesses in The Witness is hard and sometimes impossible

Yin-Yang Puzzles are NP-complete

Path Puzzles: Discrete Tomography with a Path Constraint is Hard

Recursed is not Recursive: A Jarring Result

Complexity of Solo Chess with Unlimited Moves


"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021

Pre-training Transformers for Knowledge Graph Completion


ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation

Learning a Simple and Effective Model for Multi-turn Response Generation with Auxiliary Tasks

Open Domain Dialogue Generation with Latent Images

Emotional conversation generation with heterogeneous graph neural network

An Empirical Study on Deep Neural Network Models for Chinese Dialogue Generation

Which Kind Is Better in Open-domain Multi-turn Dialog,Hierarchical or Non-hierarchical Models? An Empirical Study

Anna: A Dapper Open-Domain Dialogue Agent Based on a Joint Attention Network


The Continual Learning in Multimodality Benchmark

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks

I2I: Initializing Adapters with Improvised Knowledge


(WIP) best-practices workflow for rare disease

A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w(1118); iso-2; iso-3

Twelve years of SAMtools and BCFtools

Nextflow enables reproducible computational workflows

Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications

A universal SNP and small-indel variant caller using deep neural networks

BCFtools/csq: haplotype-aware variant consequences

HTSlib: C library for reading/writing high-throughput sequencing data

igv.js: an embeddable JavaScript implementation of the Integrative Genomics Viewer (IGV)

Paragraph: A graph-based structural variant genotyper for short-read sequence data

A unified haplotype-based method for accurate and comprehensive variant calling


Intensity Scan Context based full SLAM implementation for autonomous driving. ICRA 2020

Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection

International Conference on Robotics and Automation

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

NDD: A 3D Point Cloud Descriptor Based on Normal Distribution for Loop Closure Detection

NDT-Map-Code: A 3D global descriptor for real-time loop closure detection in lidar SLAM


Code of "3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces"

3D Generative Model Latent Disentanglement via Local Eigenprojection


QuickerADC is an implementation of highly-efficient product quantizers leveraging SIMD shuffle instructions integrated into FAISS

Product Quantization for Nearest Neighbor Search

Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs

The Inverted Multi-Index

Accelerated Nearest Neighbor Search with Quick ADC

PROCEEDINGS OF THE 2017 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL (ICMR'17)

Quicker ADC : Unlocking the Hidden Potential of Product Quantization With SIMD


[BMVC2023] Widely Applicable Strong Baseline for Sports Ball Detection and Tracking

TrackNetV2: Efficient Shuttlecock Tracking Network

2020 International Conference on Pervasive Artificial Intelligence (ICPAI)

MonoTrack: Shuttle trajectory reconstruction from monocular badminton video

DeepBall: Deep Neural-Network Ball Detector

Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup

PROCEEDINGS OF THE 2ND INTERNATIONAL WORKSHOP ON MULTIMEDIA CONTENT ANALYSIS IN SPORTS, MMSPORTS 2019


A Comprehensive Assessment of Dialog Evaluation Metrics

Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges

What is wrong with you?: Leveraging User Sentiment for Automatic Dialog Evaluation

FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation

EnDex: Evaluation of Dialogue Engagingness at Scale


Improved Training of Wasserstein GANs

Transferring GANs: generating images from limited data

Memory Replay GANs: learning to generate images from new categories without forgetting

Memory Replay GANs: Learning to Generate New Categories without Forgetting

FoCL: Feature-Oriented Continual Learning for Generative Models

Match What Matters: Generative Implicit Feature Replay for Continual Learning.


A simple way to calibrate your neural network.

On Calibration of Modern Neural Networks

Non-Parametric Outlier Synthesis

Overinterpretation reveals image classification model pathologies

Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction

What Makes Graph Neural Networks Miscalibrated?

Clumpiness: time-domain classification of red giant evolutionary states

Monthly notices of the Royal Astronomical Society

Unifying Model Explainability and Robustness via Machine-Checkable Concepts

Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks

Adaptive Calibrator Ensemble for Model Calibration under Distribution Shift

On Evaluating Explanation Utility for Human-AI Decision Making in NLP


An evolutionary context-integrated deep learning framework for protein engineering

SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering

Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks

Ensemble Learning with Supervised Methods Based on Large-Scale Protein Language Models for Protein Mutation Effects Prediction

International journal of molecular sciences


An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.

Interpretable Models for Granger Causality Using Self-explaining Neural Networks

A Survey on Causal Discovery Methods for I.I.D. and Time Series Data

Bayesian Spillover Graphs for Dynamic Networks


R package plspm

Multigroup Analysis using SmartPLS: Step-by-Step Guidelines for Business Research

Hidden danger: Unexpected scenario in the vector-parasite dynamics of leishmaniases in the Brazil side of triple border (Argentina, Brazil and Paraguay)

Contrasting responses of soil microbial biomass and extracellular enzyme activity along an elevation gradient on the eastern Qinghai-Tibetan Plateau

Plant-Soil Mediated Effects of Long-Term Warming on Soil Nematodes of Alpine Meadows on the Qinghai–Tibetan Plateau

Analyzing Word Embedding Through Structural Equation Modeling

PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020)

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change


A home for audio ML in JAX. Has common features, learnable frontends, pretrained supervised and self-supervised models.

mixup: Beyond Empirical Risk Minimization

A ConvNet for the 2020s

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Contrastive Learning of General-Purpose Audio Representations

LEAF: A Learnable Frontend for Audio Classification

Adapting a ConvNeXt model to audio classification on AudioSet


Switch to the sigmaexporter-plugin branch (https://github.com/oxfordinternetinstitute/gephi-plugins/tree/sigmaexporter-plugin/modules/sigmaExporter) or jsonexporter-plugin branch (https://github.com/oxfordinternetinstitute/gephi-plugins/tree/jsonexporter-plugin/modules/JsonExporter) for the relevant code.

Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer

FoxP2 isoforms delineate spatiotemporal transcriptional networks for vocal learning in the zebra finch

Growth-factor like gene regulation is separable from survival and maturation in antibody secreting cells

Mapping the Bentham Corpus: Concept-based Navigation

Journal of Data Mining and Digital Humanities

Defining common principles of gene co-expression refines molecular stratification in cancer


Code for paper "DeepEMD: Few-Shot Image Classification with Differentiable Earth Mover's Distance and Structured Classifiers", CVPR2020

Meta-learning with differentiable closed-form solvers

Fine-Grained Few-Shot Classification with Feature Map Reconstruction Networks.

Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification

DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning

Tensor feature hallucination for few-shot learning

Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning

Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations


For calculating Shapley values via linear regression.

A Unified Approach to Interpreting Model Predictions

Understanding Global Feature Contributions With Additive Importance Measures

Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression

FastSHAP: Real-Time Shapley Value Estimation

Shapley variable importance clouds for interpretable machine learning

A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study

Stochastic Amortization: A Unified Approach to Accelerate Feature and
  Data Attribution

Fast Shapley Value Estimation: A Unified Approach


Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks

Multiplicative Normalizing Flows for Variational Bayesian Neural Networks

Uncertainty-Aware Deep Classifiers using Generative Models

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

Bayesian deep learning for cosmic volumes with modified gravity


Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

Function-Space Regularization for Deep Bayesian Classification

Knowledge from Uncertainty in Evidential Deep Learning


Code for the paper Implicit Weight Uncertainty in Neural Networks

Quality of Uncertainty Quantification for Bayesian Neural Network Inference

Graceful Degradation and Related Fields


This repository documents MATLAB implementation of a dynamic user equilibrium solver, including a dynamic network loading sub-routine

Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation

Computing Dynamic User Equilibrium on Large-Scale Networks Without Knowing Global Parameters

Computing Dynamic User Equilibria on Large-Scale Networks: From Theory to Software Implementation.

Strong Convergence of Forward-Backward-Forward Methods for Pseudo-monotone Variational Inequalities with Applications to Dynamic User Equilibrium in Traffic Networks


FiLM: Visual Reasoning with a General Conditioning Layer

CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

Inferring and Executing Programs for Visual Reasoning

A Corpus for Reasoning About Natural Language Grounded in Photographs

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning

Multi-View Visual Question Answering with Active Viewpoint Selection

Measuring CLEVRness: Blackbox testing of Visual Reasoning Models


A set of treebanks for multiple languages annotated in basic Stanford-style dependencies.

Many Languages, One Parser

A Sub-Character Architecture for Korean Language Processing

A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks

International Conference on Computational Linguistics

Mutual Information Maximization for Simple and Accurate Part-Of-Speech Induction

Low-Resource Parsing with Crosslingual Contextualized Representations

Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task Learning

Compositional Morpheme Embeddings with Affixes as Functions and Stems as Arguments

RELEVANCE OF LINGUISTIC STRUCTURE IN NEURAL ARCHITECTURES FOR NLP

Apprentissage d'analyseur en dépendances cross-lingue par projection partielle de dépendances (Cross-lingual learning of dependency parsers from partially projected dependencies).


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


Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable

End-to-End Beam Retrieval for Multi-Hop Question Answering

Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering

Triggering Multi-Hop Reasoning for Question Answering in Language Models using Soft Prompts and Random Walks


Awesome resources for artificial intelligence in cardiology

Cardiovascular Event Prediction by Machine Learning

Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing

Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI

Real‐time cardiovascular MR with spatio‐temporal artifact suppression using deep learning–proof of concept in congenital heart disease

Machine Learning Approaches in Cardiovascular Imaging

Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology

A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings


PyTorch Implementation for "Deep Anomaly Detection on Attributed Networks" (SDM2019)

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

Generative Semi-supervised Graph Anomaly Detection

Region Anomaly Detection via Spatial and Semantic Attributed Graph in Human Monitoring


Polish BERT

HerBERT: Efficiently Pretrained Transformer-based Language Model for Polish.

Pre-training Polish Transformer-based Language Models at Scale

The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task

International Workshop/Conference on Parsing Technologies

Detection of Criminal Texts for the Polish State Border Guard


Code for our CVPR 2021 Paper "Self-Supervised Learning for Semi-Supervised Temporal Action Proposal".

SlowFast Networks for Video Recognition

Proposal Relation Network for Temporal Action Detection

CBR-Net: Cascade Boundary Refinement Network for Action Detection: Submission to ActivityNet Challenge 2020 (Task 1)


[TMC 2024] FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence

Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation

FedICT: Federated Multi-task Distillation for Multi-access Edge Computing

Improving Communication Efficiency of Federated Distillation via Accumulating Local Updates

FedCache 2.0: Exploiting the Potential of Distilled Data in Knowledge Cache-driven Federated Learning


Scene Graph Generation: A Comprehensive Survey

SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition

Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D

2.5D Visual Relationship Detection


A Survey on Session-based Recommender Systems

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation

Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations

Deep Learning-Based Sequential Recommender Systems: Concepts, Algorithms, and Evaluations


Source code for the paper "Growing urban bicycle networks", exploring algorithmically the limitations of urban bicycle network growth

Growing urban bicycle networks


Notes on single-cell Hi-C technologies, tools, and data

Single-cell Hi-C reveals cell-to-cell variability in chromosome structure

Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells

3D structures of individual mammalian genomes studied by single-cell Hi-C

Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition

Cell-cycle dynamics of chromosomal organization at single-cell resolution

Cell cycle dynamics of chromosomal organisation at single-cell resolution

Massively multiplex single-cell Hi-C

Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin

Zenodo (CERN European Organization for Nuclear Research)

Three-dimensional genome structures of single diploid human cells

Simultaneous profiling of 3D genome structure and DNA methylation in single human cells


An air travel dataset consisting of user reviews from Skytrax (www.airlinequality.com)

Goal Driven Discovery of Distributional Differences via Language Descriptions

Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data

Cross-Domain Sentiment Classification with In-Domain Contrastive Learning

High Enough? Explaining and Predicting Traveler Satisfaction Using Airline Review

Towards Sentence Level Inference Attack Against Pre-trained Language Models

Proceedings on Privacy Enhancing Technologies


Code and data for IJCAI-17 paper Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

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

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned

An Adversarial Transfer Network for Knowledge Representation Learning


Explainability for Vision Transformers

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

Training data-efficient image transformers & distillation through attention

Quantifying Attention Flow in Transformers

Epileptic seizure detection by using interpretable machine learning models

Pedestrian Attribute Recognition via CLIP based Prompt Vision-Language Fusion

Spatio-Temporal Side Tuning Pre-trained Foundation Models for Video-based Pedestrian Attribute Recognition


PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"

A Differential Entropy Estimator for Training Neural Networks

Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space

Variational f-Divergence and Derangements for Discriminative Mutual Information Estimation


(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"

FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning


Implementation for IGCN and GLP model in our paper "Label Efficient Semi-Supervised Learning via Graph Filtering."

Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity

How Powerful is Implicit Denoising in Graph Neural Networks


PyTorch implementations of NVDM, GSM, NTM, NTMR

Neural Variational Inference for Text Processing

Discovering Discrete Latent Topics with Neural Variational Inference

Coherence-Aware Neural Topic Modeling

Classification aware neural topic model for COVID-19 disinformation categorisation

vONTSS: vMF based semi-supervised neural topic modeling with optimal transport

DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM


Online Multi-Granularity Distillation for GAN Compression (ICCV2021)

Information-Theoretic GAN Compression with Variational Energy-based Model


AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos. ECCV'18.

Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization

UntrimmedNets for Weakly Supervised Action Recognition and Detection

Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images

MM'15: PROCEEDINGS OF THE 2015 ACM MULTIMEDIA CONFERENCE


(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

How Do Vision Transformers Work?

Vector Quantized Bayesian Neural Network Inference for Data Streams


Neural Paiters

Very Deep Convolutional Networks for Large-Scale Image Recognition

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

A Neural Algorithm of Artistic Style

Neural Painters: A learned differentiable constraint for generating brushstroke paintings


Repository for the Stanford Knee MRI Multi-Task Evaluation (SKM-TEA) Dataset

SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation

Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning

Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers


Implementation and demonstration of the paper: Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection

DeepFake-o-meter: An Open Platform for DeepFake Detection

How Generalizable are Deepfake Image Detectors? An Empirical Study


CPU/GPU/TPU implementation of the Inception Score

Improved Techniques for Training GANs

Content-Aware GAN Compression

Measuring the Transferability of Adversarial Examples

Generative Models with Information-Theoretic Protection Against Membership Inference Attacks


Code and dataset for paper "Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts" published in KDD'2019.

Type-augmented Relation Prediction in Knowledge Graphs

KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and Completion


Author's PyTorch implementation of BCQ for continuous and discrete actions

Off-Policy Deep Reinforcement Learning without Exploration

D4RL: Datasets for Deep Data-Driven Reinforcement Learning

An Optimistic Perspective on Offline Reinforcement Learning

Planning with Diffusion for Flexible Behavior Synthesis

Benchmarking Batch Deep Reinforcement Learning Algorithms

PLAS: Latent Action Space for Offline Reinforcement Learning

d3rlpy: An Offline Deep Reinforcement Learning Library

Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning

Mildly Conservative Q-Learning for Offline Reinforcement Learning

Safe Model-Based Off-Policy Reinforcement Learning for Eco-Driving in Connected and Automated Hybrid Electric Vehicles


[RAL 2022 & ICRA 2023] TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and A Grasping Baseline

TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baseline

Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation

Tabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Prior


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

Virtual Reality International Conference

Dialectical polyptych: an interactive movie


Annotated dataset of 100 works of fiction to support tasks in natural language processing and the computational humanities.

An Annotated Dataset of Coreference in English Literature

Literary Event Detection

Meeting of the Association for Computational Linguistics

Named Entity Recognition and Classification in Historical Documents: A Survey

An annotated dataset of literary entities

North American Chapter of the Association for Computational Linguistics

Measuring Information Propagation in Literary Social Networks

The Project Dialogism Novel Corpus: A Dataset for Quotation Attribution in Literary Texts

Improving Automatic Quotation Attribution in Literary Novels

Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective

Computational Storytelling and Emotions: A Survey

Comparing Annotated Datasets for Named Entity Recognition in English Literature

LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION


基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型，进行下游具体任务微调，涉及Freeze、Lora、P-tuning、全参微调等

LoRA: Low-Rank Adaptation of Large Language Models

GPT Understands, Too

P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks


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

RamanNet: a generalized neural network architecture for Raman spectrum analysis

RamanNet: a lightweight convolutional neural network for bacterial identification based on Raman spectra

Towards Knowledge Uncertainty Estimation for Open Set Recognition

Machine Learning and Knowledge Extraction

Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets

IEEE journal of biomedical and health informatics


The code of Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation

Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation

Evaluating progress in automatic chest X-ray radiology report generation

Radiology-Aware Model-Based Evaluation Metric for Report Generation

The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It


VED (Vehicle Energy Dataset): A Large-scale Dataset for Vehicle Energy Consumption Research. (IEEE Transactions on Intelligent Transportation Systems, 2020)

Vehicle Energy Dataset (VED), A Large-Scale Dataset for Vehicle Energy Consumption Research

Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook

A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Investigating the Spatiotemporal Charging Demand and Travel Behavior of Electric Vehicles Using GPS Data: A Machine Learning Approach


It'll detect your anomalies! Part of the Kale stack.

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

International Conference on Machine Learning and Applications

Real-Time Anomaly Detection for Streaming Analytics

Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks

Neural networks : the official journal of the International Neural Network Society

Multivariate-Time-Series-Driven Real-time Anomaly Detection Based on Bayesian Network

Neuroscience-Inspired Algorithms for the Predictive Maintenance of Manufacturing Systems

IEEE Transactions on Industrial Informatics

A Review of Open Source Software Tools for Time Series Analysis


Pytorch porting of C3D network, with Sports1M weights

Leveraging Random Label Memorization for Unsupervised Pre-Training

What Matters for Ad-hoc Video Search? A Large-scale Evaluation on TRECVID

Video Language Co-Attention with Multimodal Fast-Learning Feature Fusion for VideoQA

Workshop on Representation Learning for NLP


Official Implementation of Neural Splines

FALKON: An Optimal Large Scale Kernel Method

POCO: Point Convolution for Surface Reconstruction

On the Similarity between the Laplace and Neural Tangent Kernels

Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks


Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

Barking up the right tree: an approach to search over molecule synthesis DAGs

Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization

An Unpooling Layer for Graph Generation


Meta-Learning with Warped Gradient Descent

BOIL: Towards Representation Change for Few-shot Learning

Transferring Knowledge across Learning Processes

Graceful Degradation and Related Fields


Pytorch implementation of R-BERT: "Enriching Pre-trained Language Model with Entity Information for Relation Classification"

Knowledge-Augmented Language Models for Cause-Effect Relation Classification

Improving Drug–Drug Interaction Extraction with Gaussian Noise


This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

In Search of Lost Domain Generalization

Improving Test-Time Adaptation via Shift-agnostic Weight Regularization and Nearest Source Prototypes

Test-Time Adaptation via Self-Training with Nearest Neighbor Information

Feature Alignment and Uniformity for Test Time Adaptation

Test-Time Model Adaptation with Only Forward Passes

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

Decoupled Prototype Learning for Reliable Test-Time Adaptation


Unified Concept Editing in Diffusion Models

MACE: Mass Concept Erasure in Diffusion Models

UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning
  for Diffusion Models

Erasing Concepts from Text-to-Image Diffusion Models with Few-shot Unlearning


Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

MetaPoison: Practical General-purpose Clean-label Data Poisoning


On Network Design Spaces for Visual Recognition

Generic Neural Architecture Search via Regression

Speedy Performance Estimation for Neural Architecture Search

Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis


Convolutional Sequence to Sequence Learning

Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

On Faithfulness and Factuality in Abstractive Summarization

BRIO: Bringing Order to Abstractive Summarization

SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization

A Survey of Knowledge-enhanced Text Generation

HighRES: Highlight-based Reference-less Evaluation of Summarization

RefSum: Refactoring Neural Summarization

Finding a Balanced Degree of Automation for Summary Evaluation

Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine Translation


Bayesian Optimization of Combinatorial Structures

Mercer Features for Efficient Combinatorial Bayesian Optimization

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework

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

Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems

Communications in computer and information science

Scalable Combinatorial Bayesian Optimization with Tractable Statistical models


Pytorch implementation of BERT4Rec and Netflix VAE.

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

Variational Autoencoders for Collaborative Filtering

Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect

A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation

From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users

Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions

SLMRec: Empowering Small Language Models for Sequential Recommendation


Exposure Matrix Factorization: modeling user exposure in recommendation

Modeling User Exposure in Recommendation

Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback

From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation


Code for "Temporal Difference Learning for Model Predictive Control"

TD-MPC2: Scalable, Robust World Models for Continuous Control

One Policy to Dress Them All: Learning to Dress People with Diverse Poses and Garments

MoVie: Visual Model-Based Policy Adaptation for View Generalization

Reparameterized Policy Learning for Multimodal Trajectory Optimization

IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control

Simplified Temporal Consistency Reinforcement Learning

Sample-efficient Real-time Planning with Curiosity Cross-Entropy Method and Contrastive Learning


Reinforcement learning for medical decisions

A Conservative Q-Learning approach for handling distribution shift in sepsis treatment strategies

Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies


High-accuracy NLP parser with models for 11 languages.

Constituency Parsing with a Self-Attentive Encoder

FlauBERT: Unsupervised Language Model Pre-training for French

Multilingual Constituency Parsing with Self-Attention and Pre-Training

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little

Unsupervised Recurrent Neural Network Grammars

Graph Convolutions over Constituent Trees for Syntax-Aware Semantic Role Labeling

Cross-Domain Generalization of Neural Constituency Parsers

Constituency Lattice Encoding for Aspect Term Extraction

International Conference on Computational Linguistics

Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization

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

FlauBERT : des modèles de langue contextualisés pré-entraînés pour le français (FlauBERT : Unsupervised Language Model Pre-training for French)


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

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

Identification of M2-like macrophage-related signature for predicting the prognosis, ecosystem and immunotherapy response in hepatocellular carcinoma

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

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

Machine learning-based cell death signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma

Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma


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


[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations

Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement

Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces

Interactive exploration of design trade-offs

Pareto Set Learning for Expensive Multi-Objective Optimization

Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations

A Parallel Technique for Multi-objective Bayesian Global Optimization: Using a Batch Selection of Probability of Improvement


Point cloud diffusion for 3D model synthesis

Zero-1-to-3: Zero-shot One Image to 3D Object

Point-E: A System for Generating 3D Point Clouds from Complex Prompts

3DGen: Triplane Latent Diffusion for Textured Mesh Generation

Consistent-1-to-3: Consistent Image to 3D View Synthesis via Geometry-aware Diffusion Models

3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors

iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis

MicroDreamer: Zero-shot 3D Generation in ∼20 Seconds by Score-based
  Iterative Reconstruction


[Official] Exploring Temporal Coherence for More General Video Face Forgery Detection(ICCV 2021)

Detecting Deepfakes with Self-Blended Images

Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection

Generalizable Deepfake Detection with Phase-Based Motion Analysis

DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection

Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning


A fast and highly scalable GPU dynamic memory allocator

A Dynamic Hash Table for the GPU

Compiler-Assisted Workload Consolidation for Efficient Dynamic Parallelism on GPU

International Parallel and Distributed Processing Symposium


⛵ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]

Deep Residual Learning for Image Recognition

Very Deep Convolutional Networks for Large-Scale Image Recognition

Going Deeper with Convolutions

Densely Connected Convolutional Networks

Squeeze-and-Excitation Networks

Rethinking the Inception Architecture for Computer Vision

MobileNetV2: Inverted Residuals and Linear Bottlenecks

Xception: Deep Learning with Depthwise Separable Convolutions

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

Identity Mappings in Deep Residual Networks


Latent space clustering in Generative Adversarial Network (GAN)

ClusterGAN : Latent Space Clustering in Generative Adversarial Networks

Attentive Representation Learning With Adversarial Training for Short Text Clustering

K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs


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

Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation


PyTorch implementations of neural networks for timeseries classification

Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

InceptionTime: Finding AlexNet for time series classification

Efficient Architecture Search for Diverse Tasks

Vector Quantized Time Series Generation with a Bidirectional Prior Model


Parameter-Free Optimizers for Pytorch

A Modern Introduction to Online Learning

Coin Betting and Parameter-Free Online Learning

Training Deep Networks without Learning Rates Through Coin Betting

DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule

Parameter-free Stochastic Optimization of Variationally Coherent Functions


CompILE: Compositional Imitation Learning and Execution (ICML 2019)

Unsupervised Learning of Temporal Abstractions With Slot-Based Transformers

Learning Task Decomposition with Ordered Memory Policy Network


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

RA: A Static Analysis Tool for Analyzing Re-Entrancy Attacks in Ethereum Smart Contracts

A Comparative Evaluation of Automated Analysis Tools for Solidity Smart Contracts


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

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

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


Scalable implementation of DREAM - Deep RL for multi-agent imperfect information games

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Deep Counterfactual Regret Minimization

DREAM: Deep Regret minimization with Advantage baselines and Model-free learning

Single Deep Counterfactual Regret Minimization


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


Variational Graph Recurrent Neural Networks - PyTorch

Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space

HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction

A Comprehensive Survey on Graph Summarization with Graph Neural Networks


Implemetation of ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

Correcting Diffusion-Based Perceptual Image Compression with Privileged
  End-to-End Decoder

Neural Image Compression with Text-guided Encoding for both Pixel-level
  and Perceptual Fidelity


GEITje 7B: een groot open Nederlands taalmodel

Llama 2: Open Foundation and Fine-Tuned Chat Models

NEFTune: Noisy Embeddings Improve Instruction Finetuning

Language Resources for Dutch Large Language Modelling

DUMB: A Benchmark for Smart Evaluation of Dutch Models

PolygloToxicityPrompts: Multilingual Evaluation of Neural Toxic
  Degeneration in Large Language Models


inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver

Regularizing and Optimizing LSTM Language Models

An Analysis of Neural Language Modeling at Multiple Scales

Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings

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


Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset

Bag of Tricks for Image Classification with Convolutional Neural Networks

High-Performance Large-Scale Image Recognition Without Normalization


Supercharged BLIP-2 that can handle videos

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Text-Conditioned Resampler For Long Form Video Understanding

PALM: Predicting Actions through Language Models

AutoAD III: The Prequel -- Back to the Pixels


This is an implementation demo of the ICLR 2021 paper [Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks](https://openreview.net/pdf?id=9l0K4OM-oXE) in PyTorch.

Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks

Anti-Backdoor Learning: Training Clean Models on Poisoned Data

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness

Backdoor Defense via Decoupling the Training Process

Adversarial Unlearning of Backdoors via Implicit Hypergradient

BackdoorBench: A Comprehensive Benchmark of Backdoor Learning

Backdoor Attack through Frequency Domain

Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation

Backdoor Defense via Deconfounded Representation Learning


This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.

Explaining and Harnessing Adversarial Examples

Adversarial examples in the physical world

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

Boosting Adversarial Attacks with Momentum


WebRISC-V: A Web-Based Education-Oriented RISC-V Pipeline Simulation Environment [PHP]

WebRISC-V: a Web-Based Education-Oriented RISC-V Pipeline Simulation Environment

Workshop On Computer Architecture Education


Compendium of available lists of ligand-receptor pairs and surface-secreted protein interactions.

Systems Biology of Gut Microbiota-Human Receptor Interactions: Toward Anti-inflammatory Probiotics

Alzheimer’s disease rewires gene coexpression networks coupling different brain regions

Resident and recruited macrophages differentially contribute to cardiac healing after myocardial ischemia


A minimalist implementation of score-based diffusion model

Denoising Diffusion Probabilistic Models

Score-Based Generative Modeling through Stochastic Differential Equations

Maximum Likelihood Training of Score-Based Diffusion Models

A Variational Perspective on Diffusion-Based Generative Models and Score Matching


FITS: Frequency Interpolation Time Series Analysis Baseline

FITS: Modeling Time Series with 10k Parameters

An Analysis of Linear Time Series Forecasting Models

TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly
  Detection Models

Revitalizing Multivariate Time Series Forecasting: Learnable
  Decomposition with Inter-Series Dependencies and Intra-Series Variations
  Modeling


ResNet model in TensorFlow

Deep Residual Learning for Image Recognition

Deep Networks with Stochastic Depth

Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex

Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems

Automating Morphological Profiling with Generic Deep Convolutional Networks

Ludwig: a type-based declarative deep learning toolbox

A multicenter study on two-stage transfer learning model for duct-dependent CHDs screening in fetal echocardiography


Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

Variational Transformers for Diverse Response Generation

Think Twice: A Human-like Two-stage Conversational Agent for Emotional Response Generation


Automated Detection of COVID-19 Cases Using Deep Neural Networks with X-Ray Images

Automated detection of COVID-19 cases using deep neural networks with X-ray images

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays

Computer methods and programs in biomedicine

Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study

Biomedical signal processing and control

DeepCOVIDExplainer: Explainable COVID-19 Diagnosis Based on Chest X-ray Images

Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost

Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

Initial Stage COVID-19 Detection System Based on Patients’ Symptoms and Chest X-Ray Images

SAM: Self-augmentation mechanism for COVID-19 detection using chest X-ray Images

Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images

International journal of environmental research and public health

Robust Classification and Detection of Big Medical Data Using Advanced Parallel K-Means Clustering, YOLOv4, and Logistic Regression


Official implementation of paper "One-dimensional Adapter to Rule Them All: Concepts, Diffusion Models and Erasing Applications".

UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning
  for Diffusion Models

Erasing Concepts from Text-to-Image Diffusion Models with Few-shot Unlearning


MSRS: Multi-Spectral Road Scenarios for Practical Infrared and Visible Image Fusion

Infrared and Visible Image Fusion: Methods, Datasets, Applications, and Prospects

The Effect of Data Augmentation Methods on Pedestrian Object Detection

IFormerFusion: Cross-Domain Frequency Information Learning for Infrared and Visible Image Fusion Based on the Inception Transformer

MJ-GAN: Generative Adversarial Network with Multi-Grained Feature Extraction and Joint Attention Fusion for Infrared and Visible Image Fusion

InfMAE: A Foundation Model in the Infrared Modality

Image Fusion via Vision-Language Model


VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

A Survey on Neural Speech Synthesis

StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

WavThruVec: Latent speech representation as intermediate features for neural speech synthesis

StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis

Matcha-TTS: A fast TTS architecture with conditional flow matching

DiffVoice: Text-to-Speech with Latent Diffusion

The VoicePrivacy 2024 Challenge Evaluation Plan

SNAC: Speaker-Normalized Affine Coupling Layer in Flow-Based Architecture for Zero-Shot Multi-Speaker Text-to-Speech

Lightweight and High-Fidelity End-to-End Text-to-Speech with Multi-Band Generation and Inverse Short-Time Fourier Transform


a signal-level demultiplexer for Oxford Nanopore reads

Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks

Molecular barcoding of native RNAs using nanopore sequencing and deep learning

Third generation sequencing revises the molecular karyotype for Toxoplasma gondii and identifies emerging copy number variants in sexual recombinants

Horizontal Gene Transfer and Fusion Spread Carotenogenesis Among Diverse Heterotrophic Protists

Do You Want to Build a Genome? Benchmarking Hybrid Bacterial Genome Assembly Methods


Single Hyperspectral Image Denoising, Inpainting, Super-Resolution

Hyperspectral Image Super-Resolution with Self-Supervised Spectral-Spatial Residual Network

Coupling Model- and Data-Driven Methods for Remote Sensing Image Restoration and Fusion: Improving physical interpretability

Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution

A General Destriping Framework for Remote Sensing Images Using Flatness Constraint


conlleval in Python (script for chunking/NER evaluation)

A Survey of Joint Intent Detection and Slot Filling Models in Natural Language Understanding

Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-context Setting

Extended Multilingual Protest News Detection - Shared Task 1, CASE 2021 and 2022

Few-shot sequence labeling with label dependency transfer

NSURL-2019 Task 7: Named Entity Recognition (NER) in Farsi

Learning Functions to Study the Benefit of Multitask Learning

F10-SGD: Fast Training of Elastic-net Linear Models for Text Classification and Named-entity Recognition

Utilizing coarse-grained data in low-data settings for event extraction


Balsa is a learned SQL query optimizer. It tailor optimizes your SQL queries to find the best execution plans for your hardware and engine.

Balsa: Learning a Query Optimizer Without Expert Demonstrations

Proceedings of the 2022 International Conference on Management of Data

Lero: A Learning-to-Rank Query Optimizer


Codebase for evaluation of deep generative models as presented in Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

Analyzing and Improving the Training Dynamics of Diffusion Models

DOCCI: Descriptions of Connected and Contrasting Images

ZigMa: A DiT-style Zigzag Mamba Diffusion Model

Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability

Consistency Models Made Easy


[TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training

Learning from Noisy Labels with Deep Neural Networks: A Survey

Bag of Tricks for Adversarial Training

Self-Adaptive Training: beyond Empirical Risk Minimization

An Alternative Surrogate Loss for PGD-based Adversarial Testing

Self-Adaptive Training: Bridging Supervised and Self-Supervised Learning

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness


Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)

Slimmable Neural Networks

Fully Convolutional Networks for Panoptic Segmentation


Attention Is All You Need

Squeeze-and-Excitation Networks

Conv-TasNet: Surpassing Ideal Time–Frequency Magnitude Masking for Speech Separation

IEEE/ACM transactions on audio, speech, and language processing

FRCRN: Boosting Feature Representation Using Frequency Recurrence for Monaural Speech Enhancement

Monaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency Losses


Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget

The Tsetlin Machine - A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

The Convolutional Tsetlin Machine

The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment

Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling

Measuring the Novelty of Natural Language Text Using the Conjunctive Clauses of a Tsetlin Machine Text Classifier

On the Convergence of Tsetlin Machines for the XOR Operator

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks


AFAD Tarballs

Deep neural networks for rank-consistent ordinal regression based on conditional probabilities

Universal Domain Adaptation in Ordinal Regression


Official code for Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection (CVPR 2022 oral)

Block shuffling learning for Deepfake Detection

How Generalizable are Deepfake Image Detectors? An Empirical Study


Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)

Variational Graph Auto-Encoders

Simple and Effective Graph Autoencoders with One-Hop Linear Models


Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning

Reinforcement-based denoising of distantly supervised NER with partial annotation

Empirical Methods in Natural Language Processing


Promting Whisper for Audio-Visual Speech Recognition, Code-Switched Speech Recognition, and Zero-Shot Speech Translation

How2: A Large-scale Dataset for Multimodal Language Understanding

Prompting the Hidden Talent of Web-Scale Speech Models for Zero-Shot Task Generalization

ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation

AVATAR: Unconstrained Audiovisual Speech Recognition


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

Learning Disentangled Representations of Video with Missing Data

ARMA Nets: Expanding Receptive Field for Dense Prediction