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2021-11-07     Blog-2021 A Gentle Introduction to Graph Neural Networks 2022-02-07     Blog-2022 Novelty in Science

2022-08-14     BookNote 《洞穴奇案》

2022-02-27     PyTorch-matmul函数 2024-11-19     面向非完备数据集的深度学习

2022-12-09     DNA Replication and Repair

2022-10-14     20221014-图神经网络的关键技术及应用前景MeetingNote

2022-04-02     Stanford-2022 AI Index Report 2022-01-08     Nature-2021 Advancing mathematics by guiding human intuition with AI 2022-06-15     ICML-2017 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks 2022-11-19     OpenAI-2022 Robust Speech Recognition via Large-Scale Weak Supervision 2023-12-31     A joint embedding of protein sequence and structure enables robust variant effect predictions 2023-03-19     Bioinformatics-2023 Accurate and efficient protein sequence design through learning concise local environment of residues 2023-05-21     bioRxiv-2023 Ankh：Optimized Protein Language Model Unlocks General-Purpose Modelling 2022-10-07     PNAS-2021 Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences 2023-11-19     ICLRw-2022 Convolutions are competitive with transformers for protein sequence pretraining 2023-09-16     Nucleic Acids Research-2022 DeepLoc 2.0：multi-label subcellular localization prediction using protein language models 2022-12-09     Bioinformatics-2021 DNABERT：pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome 2023-09-16     Bioinformatics-2017 DeepLoc：prediction of protein subcellular localization using deep learning 2023-03-27     International Journal of Molecular Sciences-2023 DeepTP：A Deep Learning Model for Thermophilic Protein Prediction 2024-08-23     ICLR-2020 DivideMix：Learning with Noisy Labels as Semi-supervised Learning 2024-02-05     ICML-2021 E(n) Equivariant Graph Neural Networks 2024-05-29     Bioinformatics-2024 Embedding-based alignment：combining protein language models with dynamic programming alignment to detect structural similarities in the twilight-zone 2023-05-01     Human Genetics-2022 Embeddings from protein language models predict conservation and variant effects 2023-11-19     ICLRw-2023 Enhancing Protein Language Models with Structure-based Encoder and Pre-training 2022-09-29     NIPS-2019 Evaluating Protein Transfer Learning with TAPE 2024-07-28     Evaluating the representational power of pre-trained DNA language models for regulatory genomics 2023-08-08     NIPS-2021 FLIP：Benchmark tasks in fitness landscape inference for proteins 2024-02-12     Nature Biotechnology-2023 Fast and accurate protein structure search with FoldseekFast and accurate protein structure search with Foldseek 2024-04-27     Fast protein structure searching using structure graph embeddings 2024-07-15     Feature Reuse and Scaling：Understanding Transfer Learning with Protein Language Models 2022-01-21     Nature-2021 Highly accurate protein structure prediction with AlphaFold 2023-03-14     NIPS-2021 Language models enable zero-shot prediction of the effects of mutations on protein function 2022-10-08     bioRxiv-2022 Language models of protein sequences at the scale of evolution enable accurate structure prediction 2023-01-24     ICLR-2021 Learning from Protein Structure with Geometric Vector Perceptrons 2022-11-16     Nature Machine Intelligence-2022 Learning functional properties of proteins with language models 2023-02-02     ICML-2021 Learning inverse folding from millions of predicted structures 2023-08-04     Nature Biotechnology-2022 Learning protein fitness models from evolutionary and assay-labeled data 2024-01-02     Learning sequence, structure, and function representations of proteins with language models 2023-11-19     Bioinformatics Advances-2021 Light attention predicts protein location from the language of life 2022-10-03     ICML-2021 MSA Transformer 2024-02-03     ACS Synthetic Biology-2019 Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima 2023-01-18     bioRxiv-2022 Masked inverse folding with sequence transfer for protein representation learning 2022-11-08     KDD-2021 Modeling Protein Using Large-scale Pretrain Language Model 2024-10-07     Nature Biotechnology-2024 Multistate and functional protein design using RoseTTAFold sequence space diffusion 2022-11-09     ICLR-2022 OntoProtein：Protein Pretraining With Gene Ontology Embedding 2023-09-30     NIPS-2022 PEER：A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding 2024-06-25     Nature Communications-2024 PLMSearch：Protein language model powers accurate and fast sequence search for remote homology 2023-06-19     PoET：A generative model of protein families as sequences-of-sequences 2022-11-17     TPAMI-2020 ProtTrans：Towards Cracking the Language of Life’s Code Through Self-Supervised Learning 2023-09-30     Protein generation with evolutionary diffusion：sequence is all you need 2024-04-30     Nature Biotechnology-2024 Protein remote homology detection and structural alignment using deep learning 2023-12-30     NeurIPS-2023 ProteinGym：Large-Scale Benchmarks for Protein Design and Fitness Prediction 2024-04-04     ICLR-2023 SaProt：Protein Language Modeling with Structure-aware Vocabulary 2024-06-13     eLife-2024 Sensitive remote homology search by local alignment of small positional embeddings from protein language models 2024-07-01     Simulating 500 million years of evolution with a language model 2022-11-09     Nature Biotechnology-2022 Single-sequence protein structure prediction using a language model and deep learning 2023-07-19     Nature Machine Intelligence-2023 Structure-inducing pre-training 2023-06-11     Structure-informed Language Models Are Protein Designers 2024-01-31     JCIM-2024 TM-search：An Efficient and Effective Tool for Protein Structure Database Search 2023-01-17     bioRxiv-2021 Toward More General Embeddings for Protein Design：Harnessing Joint Representations of Sequence and Structure 2023-03-14     ICML-2022 Tranception：protein fitness prediction with autoregressive transformers and inference-time retrieval 2023-01-09     bioRxiv-2023 When Geometric Deep Learning Meets Pretrained Protein Language Models 2023-03-27     Frontiers in Microbiology-2022 iThermo：A Sequence-Based Model for Identifying Thermophilic Proteins Using a Multi-Feature Fusion Strategy 2021-11-02     NIPS-2017 Attention Is All You Need 2022-10-29     NIPS-2022 Chain of Thought Prompting Elicits Reasoning in Large Language Models 2021-11-23     ACL-2019 BERT：Pre-training of Deep Bidirectional Transformers for Language Understanding 2022-02-07     AAAI-2018 Generative Adversarial Network for Abstractive Text Summarization 2021-12-23     ICLR-2019 Graph2Seq：Graph to Sequence Learning with Attention-based Neural Networks 2022-09-05     CVPR-2022 Grounded Language-Image Pre-trainin 2023-02-12     arXiv-2022 Holistic Evaluation of Language Models 2022-10-23     ACL-2018 Improving Abstraction in Text Summarization 2022-03-21     NIPS-2018 Improving Language Understanding by Generative Pre-Training 2022-05-11     ACL-2019 Improving Robustness of Neural Machine Translation with Multi-task Learning 2022-03-21     OpenAI-2020 Language Models are Few-Shot Learners 2022-03-21     ICML-2019 Language Models are Unsupervised Multitask Learners 2022-09-03     ICLR-2022 Language-driven Semantic Segmentation 2022-02-28     ACL-2021 Learning Sequential and Structural Information for Source Code Summarization 2022-06-24     arXiv-2022 Learning code summarization from a small and local dataset 2023-08-06     ICLR-2022 LoRA：Low-Rank Adaptation of Large Language Models 2022-12-17     NAACL-2022 MoEBERT：from BERT to Mixture-of-Experts via Importance-Guided Adaptation 2023-03-26     ICML-2019 Parameter-Efficient Transfer Learning for NLP 2022-05-12     EMNLP-2021 Rethinking Data Augmentation for Low-Resource Neural Machine Translation：A Multi-Task Learning Approach 2022-08-20     arXiv-2019 RoBERTa：A Robustly Optimized BERT Pretraining Approach 2022-02-09     AAAI-2017 SeqGAN：Sequence Generative Adversarial Nets with Policy Gradient 2021-11-29     NIPS-2014 Sequence to Sequence Learning with Neural Networks 2022-11-13     ICLR-2021 Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning 2022-11-12     JMLR-2022 Switch Transformers：Scaling to Trillion Parameter Models with Simple and Efficient Sparsity 2023-03-15     arXiv-2022 Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback 2023-01-07     OpenAI-2022 Training language models to follow instructions with human feedback 2022-11-12     NIPS-2019 Unified Language Model Pre-training for Natural Language Understanding and Generation 2022-05-02     CVPR-2018 A Closer Look at Spatiotemporal Convolutions for Action Recognition 2022-01-12     ICML-2020 A Simple Framework for Contrastive Learning of Visual Representations 2023-03-26     ICLR-2023 AIM：Adapting Image Models for Efficient Video Action Recognition 2022-09-17     arXiv-2021 ActionCLIP：A New Paradigm for Video Action Recognition 2022-12-12     NIPS-2021 Align before Fuse：Vision and Language Representation Learning with Momentum Distillation 2022-02-01     ICCV-2021 An Empirical Study of Training Self-Supervised Vision Transformers 2021-12-08     ICLR-2021 An Image is Worth 16x16 Words：Transformers for Image Recognition at Scale 2022-09-17     GCPR-2021 AudioCLIP：Extending CLIP to Image, Text and Audio 2023-01-14     ICML-2022 BLIP：Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation 2022-01-24     NIPS-2020 BYOL works even without batch statistics 2022-04-17     CVPR-2015 Beyond Short Snippets：Deep Networks for Video Classification 2022-01-16     NIPS-2020 Big Self-Supervised Models are Strong Semi-Supervised Learners 2022-01-21     NIPS-2020 Bootstrap your own latent：A new approach to self-supervised Learning 2022-09-17     arXiv-2021 CLIP4Clip：An Empirical Study of CLIP for End to End Video Clip Retrieval 2022-09-17     SIGGRAPH-2022 CLIPasso：Semantically-Aware Object Sketching 2022-09-17     DeepAI-2022 Can Language Understand Depth？ 2023-01-15     NIPS-2022 CoCa：Contrastive Captioners are Image-Text Foundation Models 2022-11-22     ECCV-2022 Contrastive Deep Supervision 2022-01-02     ECCV-2020 Contrastive Multiview Coding 2022-04-17     CVPR-2016 Convolutional Two-Stream Network Fusion for Video Action Recognition 2021-11-13     CVPR-2015 Deep Residual Learning for Image Recognition 2022-02-04     ICCV-2021 Emerging Properties in Self-Supervised Vision Transformers 2022-06-10     ECCV-2020 End-to-End Object Detection with Transformers 2022-01-27     CVPR-2020 Exploring Simple Siamese Representation Learning 2022-09-05     arXiv-2022 GLIPv2：Unifying Localization and Vision-Language Understanding 2021-11-19     NIPS-2014 Generative Adversarial Nets 2022-09-04     CVPR-2022 GroupViT：Semantic Segmentation Emerges from Text Supervision 2022-07-08     OpenAI-2022 Hierarchical Text-Conditional Image Generation with CLIP Latents 2022-09-17     arXiv-2021 How Much Can CLIP Benefit Vision-and-Language Tasks？ 2023-01-15     NIPS-2022 Image as a Foreign Language：BEiT Pretraining for All Vision and Vision-Language Tasks 2021-11-06     NIPS-2012 ImageNet classification with deep convolutional neural networks 2022-01-10     CVPR-2020 Improved Baselines with Momentum Contrastive Learning 2021-12-09     NIPS-2021 Intriguing Properties of Vision Transformers 2022-05-02     ICML-2021 Is Space-Time Attention All You Need for Video Understanding 2022-04-17     CVPR-2014 Large-scale Video Classification with Convolutional Neural Networks 2022-05-02     ICCV-2015 Learning Spatiotemporal Features with 3D Convolutional Networks 2022-02-11     ICML-2021 Learning Transferable Visual Models From Natural Language Supervision 2021-12-14     CVPR-2021 Masked Autoencoders Are Scalable Vision Learners 2023-04-04     WACV-2023 MixGen：A New Multi-Modal Data Augmentation 2021-12-22     CVPR-2020 Momentum Contrast for Unsupervised Visual Representation Learning 2022-05-02     CVPR-2018 Non-local Neural Networks 2022-09-05     ICLR-2022 Open-vocabulary Object Detection via Vision and Language Knowledge Distillation 2023-11-26     ICML-2022 Perceiver IO：A General Architecture for Structured Inputs & Outputs 2023-11-19     ICML-2021 Perceiver：General Perception with Iterative Attention 2022-09-17     CVPR-2022 PointCLIP：Point Cloud Understanding by CLIP 2022-04-04     CVPR-2017 Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset 2022-01-04     NIPS-2019 Representation Learning with Contrastive Predictive Coding 2022-05-02     ICCV-2019 SlowFast Networks for Video Recognition 2022-01-15     ICCV-2021 Swin Transformer：Hierarchical Vision Transformer using Shifted Windows 2023-02-27     arXiv-2022 T2I-Adapter：Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models 2022-04-17     ECCV-2016 Temporal Segment Networks：Towards Good Practices for Deep Action Recognition 2022-02-25     NIPS-2014 Two-Stream Convolutional Networks for Action Recognition in Videos 2022-01-22     Blog-2020 Understanding Self-Supervised and Contrastive Learning with "Bootstrap Your Own Latent"(BYOL) 2022-01-03     CVPR-2019 Unsupervised Embedding Learning via Invariant and Spreading Instance Feature 2022-01-05     CVPR-2018 Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination 2022-01-18     NIPS-2020 Unsupervised Learning of Visual Features by Contrasting Cluster Assignments 2022-12-14     NIPS-2021 VLMo：Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts 2022-07-29     ICML-2021 ViLT：Vision-and-Language Transformer Without Convolution or Region Supervision 2021-12-29     TNNLS-2019 A Comprehensive Survey on Graph Neural Networks 2022-04-28     ICML-2020 Contrastive Multi-View Representation Learning on Graphs 2022-04-07     NIPS-2020 Deep Graph Contrastive Representation Learning 2022-07-05     KDD-2020 GCC：Graph Contrastive Coding for Graph Neural Network Pre-Training 2022-07-10     NIPS-2020 Graph Contrastive Learning with Augmentations 2023-08-29     Neural Subgraph Matching 2022-12-19     NIPS-2022 A Neural Corpus Indexer for Document Retrieval 2022-06-19     ACM Computing Surveys-2022 Deep Meta-learning in Recommendation Systems：A Survey 2022-06-18     SIGIR-2020 How to Retrain Recommender System？A Sequential Meta-Learning Method 2022-06-16     KDD-2019 MeLU：Meta-Learned User Preference Estimator for Cold-Start Recommendation 2022-12-19     NIPS-2022 Transformer Memory as a Differentiable Search Index 2021-11-09     DLRS-2016 Wide & Deep Learning for Recommender Systems 2022-06-03     NIPS-2019 GPipe：Efficient Training of Giant Neural Networks using Pipeline Parallelism 2022-06-04     GTC-2020 Megatron-LM：Training Multi-Billion Parameter Language Models Using Model Parallelism 2022-05-10     Google-2022 Pathways：Asynchronous Distributed Dataflow for ML 2022-04-22     OSDI-2014 Scaling Distributed Machine Learning with the Parameter Server 2022-06-17     SC-2020 ZeRO：Memory Optimizations Toward Training Trillion Parameter Models 2021-11-16     ICML-2016 A Convolutional Attention Network for Extreme Summarization of Source Code 2022-07-24     ICPC-2021 A Multi-Modal Transformer-based Code Summarization Approach for Smart Contracts 2022-02-16     ICSE-2019 A Neural Model for Generating Natural Language Summaries of Program Subroutines 2022-02-17     ICSE-2019 A Novel Neural Source Code Representation Based on Abstract Syntax Tree 2022-09-14     arXiv-2022 A Survey of Deep Learning Models for Structural Code Understanding 2022-10-19     ACL-2020 A Transformer-based Approach for Source Code Summarization 2022-07-15     IJCNLP-2017 A parallel corpus of Python functions and documentation strings for automated code documentation and code generation 2022-08-02     ICSE-2022 AST-trans：code summarization with efficient tree-structured attention 2022-10-19     JSS-2022 Automatic source code summarization with graph attention networks 2022-03-06     ASE-2020 Automating just-in-time comment updating 2022-08-11     NAACL-2022 CODE-MVP：Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training 2022-04-24     ACL-2021 Code Summarization with Structure-induced Transformer 2022-04-06     EMNLP-2020 CodeBERT：A Pre-Trained Model for Programming and Natural Languages 2022-08-25     EMNLP-2021 CodeT5：Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation 2022-03-05     IJCAI-2019 Commit Message Generation for Source Code Changes 2022-03-23     DeepMind-2022 Competition-Level Code Generation with AlphaCode 2022-03-25     ACL-2020 Contrastive Code Representation Learning 2022-06-28     ICSE-2022 Cross-Domain Deep Code Search with Few-Shot Meta Learning 2022-06-06     ICPC-2018 Deep code comment generation 2022-06-26     ICSE-2018 Deep code search 2022-02-21     ICSME-2021 Ensemble Models for Neural Source Code Summarization of Subroutines 2022-03-22     ICML-2021 Evaluating Large Language Models Trained on Code 2022-02-06     IJCAI-2021 Graph-Augmented Code Summarization in Computational Notebooks 2022-07-12     ICML-2020 Graph-based, Self-Supervised Program Repair from Diagnostic Feedback 2022-04-18     ICLR-2021 GraphCodeBERT：Pre-training Code Representations with Data Flow 2022-02-07     ACL-2021 HAConvGNN：Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks 2022-06-08     ICPC-2022 HELoC：Hierarchical Contrastive Learning of Source Code Representation 2022-08-05     AAAI-2022 Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization 2022-06-06     ACL-2022 Impact of Evaluation Methodologies on Code Summarization 2021-12-16     MSR-2020 Improved Automatic Summarization of Subroutines via Attention to File Context 2021-12-15     ICPC-2020 Improved Code Summarization via a Graph Neural Network 2022-09-16     ACL-2015 Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks 2022-09-22     ICPC-2021 Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting 2022-06-11     ICSE-2021 InferCode：Self-Supervised Learning of Code Representations by Predicting Subtrees 2022-08-09     ICLR-2021 Language-Agnostic Representation Learning of Source Code from Structure and Context 2022-01-06     ICLR-2018 Learning to Represent Programs with Graphs 2022-10-17     ESEM-2022 MMF3：Neural Code Summarization Based on Multi-Modal Fine-Grained Feature Fusion 2022-08-08     ACL-2022 Modeling Hierarchical Syntax Structure with Triplet Position for Source Code Summarization 2022-10-26     ICSE-2022 On the Evaluation of Neural Code Summarization 2022-10-12     ISSRE-2021 Peculiar：Smart Contract Vulnerability Detection Based on Crucial Data Flow Graph and Pre-training Techniques 2021-12-02     ICPC-2021 Project-Level Encoding for Neural Source Code Summarization of Subroutines 2022-02-28     ICLR-2021 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN 2022-02-12     SIGIR-2021 Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations 2022-07-30     ICPC-2022 Self-Supervised Learning of Smart Contract Representations 2022-02-15     ICLR-2019 Structured Neural Summarization 2021-12-17     ACL-2016 Summarizing Source Code using a Neural Attention Model 2022-07-03     AAAI-2021 SynCoBERT：Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation 2022-03-30     OpenAI-2022 Text and Code Embeddings by Contrastive Pre-Training 2021-12-06     ACL-2020 Towards Context-Aware Code Comment Generation 2022-09-24     ACL-2022 UniXcoder：Unified Cross-Modal Pre-training for Code Representation 2022-07-04     NAACL-2021 Unified Pre-training for Program Understanding and Generation 2022-07-18     NIPS-2020 Unsupervised Translation of Programming Languages 2022-07-26     ICPC-2022 Zero-Shot Program Representation Learning 2021-12-12     ICLR-2019 code2seq：Generating Sequences from Structured Representations of Code 2022-04-05     POPL-2019 code2vec：Learning Distributed Representations of Code

2022-03-22     1.1 课程介绍【stanford-cs329p】 2022-03-23     1.2 数据获取【stanford-cs329p】 2022-03-23     1.3 网页数据抓取【stanford-cs329p】 2022-03-24     1.4 数据标注【stanford-cs329p】 2022-06-27     10.1 深度神经网络架构【stanford-cs329p】 2022-03-24     2.1 探索性数据分析【stanford-cs329p】 2022-04-04     2.2 数据清理【stanford-cs329p】 2022-04-04     2.3 数据变换【stanford-cs329p】 2022-04-06     2.4 特征工程【stanford-cs329p】 2022-04-06     2.5 数据科学家的日常【stanford-cs329p】 2022-04-06     3.1 8分钟机器学习介绍【stanford-cs329p】 2022-05-10     3.2 最简单也最常用的决策树【stanford-cs329p】 2022-05-10     3.3 最简单也同样最常用的线性模型【stanford-cs329p】 2022-05-12     3.4 随机梯度下降【stanford-cs329p】 2022-05-12     3.5 多层感知机【stanford-cs329p】 2022-05-12     3.6 卷积神经网络【stanford-cs329p】 2022-05-13     3.7 循环神经网络【stanford-cs329p】 2022-05-14     4.1 模型评估【stanford-cs329p】 2022-06-06     4.2 过拟合和欠拟合【stanford-cs329p】 2022-06-06     4.3 模型验证【stanford-cs329p】 2022-06-08     5.1 方差和偏差【stanford-cs329p】 2022-06-10     5.2 Bagging【stanford-cs329p】 2022-06-13     5.3 Boosting【stanford-cs329p】 2022-06-15     5.4 Stacking【stanford-cs329p】 2022-06-17     9.1 模型调参【stanford-cs329p】 2022-06-22     9.2 超参数优化【stanford-cs329p】 2022-06-26     9.3 网络架构搜索【stanford-cs329p】