awesome-graph-ml

Courses

1- Stanford CS224W / 2019 Winter Lecture Videos

2- Mcgill Comp766

3- Jian Tang

Books

1- William L. Hamilton. (2020). Graph Representation Learning. Morgan & Claypool, forthcoming

2- DLG

Collections

1- graph-based-deep-learning-literature

2- deep-learning-drizzle

3- qdata Deep Learning Readings

4- Graph Machine Learning Telegram Group

Workshops

1- GRL+ Videos

2- GRL

3- GDL Israel

4- MLG

Slides

1- Xavier Bresson tutorial_CVPR17_DL_graphs

Blog Posts

1- Michael Bronstein

2- Boris Kynazev

3- Introduction to GNNs with GatedGCN

Tutorials

1- Shunwang Gong GNN Tutorial

2- mims-harvard graphml-tutorials

Videos

1- Jure Leskovec "Deep Learning on Graphs"

2- Geometric Deep Learning - Michael Bronstein - MLSS 2020, Tübingen

3- Xavier Bresson: "Convolutional Neural Networks on Graphs"

4- Stefanie Jegelka: Representation and Learning in Graph Neural Networks

5- Focused Lecture - Graph Neural Networks with Petar Velickovic

6- Learning the Structure of Graph Neural Networks | Mathias Niepert | heidelberg.ai

Podcasts

1- TWiML Joan Bruna & Michael Bronstein Interview - Geometric Deep Learning

2- TWiML Graph ML Research at Twitter with Michael Bronstein

Tools

1- Pytorch Geometric

2- DGL

3- graph-learn