Papers

这篇笔记用于收藏别人的博客 Tech Blog Blog Author https://michael-bronstein.medium.com/ Michael Bronstein https://geometricdeeplearning.com/ Michael Bronstein https://www.notion.so/Paper-Notes-by-Vitaly-Kurin-97827e14e5cd4183815cfe3a5ecf2f4c Vitaly Kurin (Many Paper Notes) https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial1/Lisa_Cluster.html UvA DL Notebooks https://graph-neural-networks.github.io/index.html GNN Books http://prob140.org/sp17/textbook/ Probability for Data Science class at UC Berkeley https://graphreason.github.io/schedule.html Learning and Reasoning with Graph-Structured Representations ICML 2019 Workshop https://chuxuzhang.github.io/KDD21_Tutorial.html KDD2021 Tutorial: Data Efficient Learning on Graphs http://songcy.net/posts/ Changyue Song (Kernel) https://www.cs.mcgill.ca/~wlh/grl_book/ William L. Hamilton https://kexue.fm/ BoJone https://danielegrattarola.github.io/blog/ Daniele Grattarola (EPFL) https://ai.googleblog.com/2022/03/robust-graph-neural-networks.html Google AI Blog https://zhiyuchen.com/blogs/ Zhiyu Chen https://andreasloukas.blog/ Andreas Loukas (EPFL) https://irhum.pubpub.org/pub/gnn/release/4 Understanding Graph Neural Networks https://lilianweng.github.io/ Lilian Weng https://www.zhihu.com/column/marlin 深度学习与图网络 https://github.com/roboticcam/machine-learning-notes Yida Xu https://www.dgl.ai/pages/index.html DGL https://www.kexinhuang.com/tech-blog Kexin Huang https://rish16.notion.site/a8c6fcb0c29c4764afa1926ad33084f8?v=bb27bb0444574fbd85f0c9d7e43b9da8 Rishabh Anand https://saashanair.com/blog Saasha Nair http://www.huaxiaozhuan.com/ 华校专 https://github.com/dglai/WWW20-Hands-on-Tutorial DGL https://blog.csdn.net/CSDNTianJi/article/details/104195306 Meng Liu https://www.chaitjo.com/post/ Chaitanya K. Joshi https://scottfreitas.medium.com/ Scott Freitas https://fabianfuchsml.github.io/ Fabian Fuchs https://medium.com/@pantelis.elinas Pantelis Elinas https://github.com/tianyicui/pack 背包9講 https://www.fenghz.xyz/ https://sakigami-yang.me/2017/08/13/about-kernel-01/ kernel https://davidham3.github.io/blog https://fenghz.github.io/index.html https://archwalker.github.io/ Awesome-Awesomes Repo Name https://github.com/naganandy/graph-based-deep-learning-literature links to conference publications in graph-based deep learning (Very, Very, Very Important) https://github.com/SherylHYX/pytorch_geometric_signed_directed PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. https://github.com/EdisonLeeeee/Awesome-Fair-Graph-Learning Paper Lists for Fair Graph Learning https://github.com/thunlp/PromptPapers Must-read papers on prompt-based tuning for pre-trained language models. https://github.com/zhao-tong/graph-data-augmentation-papers A curated list of graph data augmentation papers. https://github.com/Thinklab-SJTU/ThinkMatch Code & pretrained models of novel deep graph matching methods. https://github.com/FLHonker/Awesome-Knowledge-Distillation Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。 https://github.com/zlpure/awesome-graph-representation-learning A curated list for awesome graph representation learning resources. https://github.com/basiralab/GNNs-in-Network-Neuroscience A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020. https://github.com/flyingdoog/awesome-graph-explainability-papers Papers about explainability of GNNs https://github.com/yuanqidu/awesome-graph-generation A curated list of graph generation papers and resources. https://github.com/benedekrozemberczki/awesome-decision-tree-papers A collection of research papers on decision, classification and regression trees with implementations. https://github.com/AstraZeneca/awesome-explainable-graph-reasoning A collection of research papers and software related to explainability in graph machine learning. https://github.com/LirongWu/awesome-graph-self-supervised-learning Awesome Graph Self-Supervised Learning https://github.com/Chen-Cai-OSU/awesome-equivariant-network Paper list for equivariant neural network https://github.com/mengliu1998/DL4DisassortativeGraphs Papers about developing DL methods on disassortative graphs https://github.com/SunQingYun1996/Graph-Reinforcement-Learning-Papers A curated list of graph reinforcement learning papers. https://github.com/ChandlerBang/awesome-self-supervised-gnn Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN). https://github.com/GRAND-Lab/Awesome-Graph-Neural-Networks Paper Lists for Graph Neural Networks https://github.com/jwzhanggy/IFMLab_GNN Graph Neural Network Models from IFM Lab https://github.com/ChandlerBang/awesome-graph-attack-papers Adversarial attacks and defenses on Graph Neural Networks. https://github.com/safe-graph/graph-adversarial-learning-literature A curated list of adversarial attacks and defenses papers on graph-structured data. https://github.com/benedekrozemberczki/awesome-graph-classification A collection of important graph embedding, classification and representation learning papers with implementations. https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers A curated list of gradient boosting research papers with implementations. https://github.com/benedekrozemberczki/awesome-community-detection A curated list of community detection research papers with implementations. https://github.com/giannifranchi/awesome-uncertainty-deeplearning This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models. https://sites.google.com/site/graphmatchingmethods/ Efficient Methods for Graph Matching and MAP Inference https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets). https://github.com/jwwthu/GNN4Traffic This is the repository for the collection of Graph Neural Network for Traffic Forecasting. https://github.com/zwt233/Awesome-Auto-GNNs A paper collection about automated graph learning https://github.com/chaitjo/awesome-efficient-gnn Efficient Graph Neural Networks - a curated list of papers and projects https://github.com/Radical3-HeZhang/Awesome-Trustworthy-GNNs Awesome Resources on Trustworthy Graph Neural Networks https://github.com/EdisonLeeeee/Awesome-Masked-Autoencoders A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.). https://github.com/XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection Awesome graph anomaly detection techniques built based on deep learning frameworks. https://github.com/mengliu1998/awesome-expressive-gnn A collection of papers studying/improving the expressiveness of graph neural networks (GNNs) Useful Repo/Tools Name Info http://acronymify.com/ Model Name https://csacademy.com/app/graph_editor/ Graph Editor https://github.com/guanyingc/python_plot_utils A simple code for plotting figure, colorbar, and cropping with python https://github.com/guanyingc/latex_paper_writing_tips Tips for Writing a Research Paper using LaTeX https://github.com/JhuoW/Pytorch_Program_Templete Pytorch Program Templete GNN https://github.com/graph4ai/graph4nlp Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources! https://github.com/benedekrozemberczki/pytorch_geometric_temporal PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021) https://github.com/ysig/GraKeL A scikit-learn compatible library for graph kernels https://github.com/jajupmochi/graphkit-learn A python package for graph kernels, graph edit distances, and graph pre-image problem. https://github.com/pliang279/awesome-phd-advice Collection of advice for prospective and current PhD students https://github.com/MLEveryday/100-Days-Of-ML-Code 100-Days-Of-ML-Code中文版 https://github.com/d2l-ai/d2l-zh 《动手学深度学习》 https://github.com/lukas-blecher/LaTeX-OCR pix2tex: Using a ViT to convert images of equations into LaTeX code. https://github.com/thunlp/OpenPrompt An Open-Source Framework for Prompt-Learning. https://github.com/snap-stanford/GraphGym Platform for designing and evaluating Graph Neural Networks (GNN) https://github.com/pygod-team/pygod A Python Library for Graph Outlier Detection (Anomaly Detection) https://github.com/MLNLP-World/Paper_Writing_Tips latex写作建议 https://github.com/dair-ai/ML-YouTube-Courses A place to discover the latest machine learning courses on YouTube. Miscellaneous Name Desc https://github.com/The-Run-Philosophy-Organization/run run学指南 https://10beasts.net/ 测评