Graph Neural Network
Links
Know-how
Video
- Stanford CS224W: Machine Learning with Graphs (Jure Leskovec, playlist)
- Stanford Graph Learning Workshop 2022 (7:57 h) - individual videos with slides
- Petar Veličković
- Graph Neural Networks
- Hussain Kara Fallah
- Machine Learning TV - not only but also GNN topics
- Hannes Stärk
- Antonio Longa - PyG tutorials
Tools & Libraries
- PyG (PyTorch Geometric) - GitHub
- currentness: well maintained
- technology: PyTorch
- GraphGym - uses PyG internaly
- DGL (Deep Graph Library) - GitHub
- currentness: well maintained
- technology: PyTorch, TensorFlow or Apache MXNet
- Spektral - GitHub
- currentness: maintained
- technology: Keras & TensorFlow 2
- Graph Nets - GitHub
- currentness: outdated, last commit Dec. 2020
- technology: Tensorflow
- arXiv paper
- Jraph - GitHub
- currentness: well maintained
- technology: JAX
Datasets
- Open Graph Benchmark (OGB)
- PyG (PyTorch Geometric) Datasets - Dataset Cheatsheet
- TUDatasets
- Benchmarking Graph Neural Networks - GitHub
Recommender Systems at Spotify
- Speaker: Andreas Damianou
- Direct Link: Stanford Graph Learning Workshop 2022
Papers mentioned
- mentioned at 2:43:40
- mentioned at 2:57:47
- Ranking systems for RecSys
- GNN architectures
- Graph-based appoaches for RecSys
- A Survey on Knowledge Graph-Based Recommender Systems (2020)
- Graph Learning based Recommender Systems: A Review (2021)
- Graph Convolutional Neural Networks for Web-Scale Recommender Systems (2018)
- Graph Convolutional Matrix Completion (2017)
- Graph Neural Networks for Social Recommendation (2019)
- Trajectory Based Podcast Recommendation (2020)
- RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation (2019)
- LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation (2020)
- KDD 2022 tutorial by El-Kishky et al. - slides
Last modified November 10, 2022: add gnn link (d79ede9)