External Resources ================== * Fey *et al.*: **PyG 2.0: Scalable Learning on Real World Graphs** [`Paper `__] * Matthias Fey and Jan E. Lenssen: **Fast Graph Representation Learning with** :pyg:`null` **PyTorch Geometric** [`Paper `_, `Slides (3.3MB) `__, `Poster (2.3MB) `__, `Notebook `__] * :stanford:`Stanford CS224W: Machine Learning with Graphs`: **Graph Machine Learning lectures** [:youtube:`null` `Youtube `__] * :stanford:`Stanford University`: **A collection of graph machine learning tutorial blog posts**, fully realized with :pyg:`null` **PyG** [`Website `__] * Soumith Chintala: **Automatic Differentiation,** :pytorch:`null` **PyTorch and Graph Neural Networks** [`Talk (starting from 26:15) `__] * Stanford University: **Graph Neural Networks using** :pyg:`null` **PyTorch Geometric** [:youtube:`null` `YouTube (starting from 33:33) `__] * Antonio Longa, Gabriele Santin and Giovanni Pellegrini: :pyg:`null` **PyTorch Geometric Tutorial** [`Website `__, :github:`null` `GitHub `__] * DAIR.AI | elvis: **Introduction to GNNs with** :pyg:`null` **PyTorch Geometric** [`Website `__, :colab:`null` `Colab `__] * Nicolas Chaulet *et al.*: **PyTorch Points 3D** - A framework for running common deep learning models for point cloud analysis tasks that heavily relies on Pytorch Geometric [:github:`null` `GitHub `__, `Documentation `__] * Weihua Hu *et al.*: :ogb:`null` **Open Graph Benchmark** - A collection of large-scale benchmark datasets, data loaders, and evaluators for graph machine learning, including :pyg:`PyG` support and examples [`Website `__, :github:`null` `GitHub `__] * **DeepSNAP** - A :pytorch:`PyTorch` library that bridges between graph libraries such as NetworkX and :pyg:`PyG` [:github:`null` `GitHub `__, `Documentation `__] * **Quiver** - A distributed graph learning library for :pyg:`PyG` [:github:`null` `GitHub `__] * Benedek Rozemberczki: **PyTorch Geometric Temporal** - A temporal GNN library built upon :pyg:`PyG` [:github:`null` `GitHub `__, `Documentation `__] * Yixuan He: **PyTorch Geometric Signed Directed** - A signed and directed GNN library built upon :pyg:`PyG` [:github:`null` `GitHub `__, `Documentation `__] * Steeve Huang: **Hands-on Graph Neural Networks with** :pytorch:`null` **PyTorch &** :pyg:`null` **PyTorch Geometric** [`Tutorial `__, `Code `__] * Francesco Landolfi: :pyg:`null` **PyTorch Geometric Tutorial** [`PDF (0.4MB) `__] * Sachin Sharma: **How to Deploy (almost) any** :pyg:`null` **PyTorch Geometric Model on Nvidia's Triton Inference Server with an Application to Amazon Product Recommendation and ArangoDB** [`Blog `__] * Amitoz Azad: **torch_pdegraph** - Solving PDEs on Graphs with :pyg:`PyG` [`Devpost `__, :github:`null` `GitHub `__] * Amitoz Azad: **Primal-Dual Algorithm for Total Variation Processing on Graphs** [`Jupyter `__] * Manan Goel: **Recommending Amazon Products using Graph Neural Networks in** :pyg:`null` **PyTorch Geometric** [:wandb:`null` `W&B Report `__] * Kùzu: **Remote Backend for** :pyg:`null` **PyTorch Geometric** [:colab:`null` `Colab `__] * Aniket Saxena: **Graph Neural Networks-based Explanation App using** :pyg:`null` **PyTorch Geometric** [`Website `__, :github:`null` `GitHub `__] * Mashaan Alshammari: **Graph Attention in** :pyg:`null` **PyTorch Geometric** [:youtube:`null` `Youtube `__, :github:`null` `GitHub `__] * Mashaan Alshammari: **Graph Convolutional Networks (GCNs) in** :pytorch:`null` **PyTorch** [:youtube:`null` `Youtube `__, :github:`null` `GitHub `__] * Mashaan Alshammari: **GCN and SGC in** :pytorch:`null` **PyTorch** [:youtube:`null` `Youtube `__, :github:`null` `GitHub `__], * Mashaan Alshammari: **GCN Variants SGC and ASGC in** :pytorch:`null` **PyTorch** [:youtube:`null` `Youtube `__, :github:`null` `GitHub `__]