Blog, Tools and Survey

Tue, 29 Mar 2022 11:03:50 +0000

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

Papers on JhuoW‘s Notes

Blog, Tools and Survey

Tech Blog

Awesome-Awesomes

Useful Repo/Tools

Miscellaneous