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Last active May 25, 2020
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Machine Learning on Graphs
  1. Graph Convolution Network - a blog post and the associated tweet. Check for the video.
  2. Deep Graph Library
  3. Machine Learning on Graphs: A Model and Comprehensive Taxonomy by Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy
  4. Relational inductive biases, deep learning, and graph networks by Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu - For the intuition of what GNNs can achieve, what the promises of the field are, together with a decent survey
  5. GNN - Curated GNN resources for Getting Starting, Tutorials, Toolkits (for different frameworks), and Research
  6. Table understanding in structured documents by Martin Holeček, Antonín Hoskovec, Petr Baudiš, Pavel Klinger
  7. Graph Neural Networks: A Review of Methods and Applications by Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, Maosong Sun
  8. A Comprehensive Survey on Graph Neural Networks by Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu
  9. A Gentle Introduction to Deep Learning for Graphs by Davide Bacciu, Federico Errica, Alessio Micheli, Marco Podda
  10. Representation Learning for Dynamic Graphs: A Survey by Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart
  11. Innovations in Graph Representation Learning - from Google AI blog
  12. What is Geometric Learning ? by Flawnsong Tong. Basic introduction to Graph Convolutions and Geometric Learning. Contains links to 3 more articles which give a very comprehensive introduction to the field of GCN.
  13. A Tale of Two Convolutions: Differing Design Paradigms for Graph Convolution Networks by Cody Marie Wild
  14. How to do Deep Learning on Graphs using Graph Convolutional Networks by Tobias Jepsen
  15. Graph Convolutional Networks by Thomas Kipf
  16. Graph based Deep Learning Literature
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