Graph Attention Networks with PyTorch Geometric

I looked into the implementation of a graph attention layer in pytorch-geometric. A graph attention network was introduced by Velickovic et al. in their paper "Graph Attention Networks". In this video, the focus is on (1) how pytorch-geometric implemented a graph attention layer (2) the expressive power of GNNs (3) training and testing graph attention on graph datasets. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🔗 notes + code: https://mashaan14.github.io/YouTube-channel/graph_neural_networks/2024_02_05_GAT ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ - website https://mashaan14.github.io/mashaan/ - github https://github.com/mashaan14 - X https://twitter.com/mashaan_14 - linkedin https://linkedin.com/in/mashaan ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ - sponsor this channel on GitHub Sponsors: https://github.com/sponsors/mashaan14 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 📹 Video edit: Adobe Premiere Rush 🎧 Audio enhancement: Adobe Podcast ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Chapters: 0:00 start 0:15 reading the paper 1:52 visualizing multi head graph attention 2:43 GATConv layer in pytorch-geometric 3:25 class GATConv 5:00 coding a graph attention layer 5:35 creating a synthetic dataset 6:08 create Data instance for pytorch-geometric 6:41 creating an instance of class GATConv 7:04 train and test functions 7:19 training graph attention 7:57 training an MLP 8:26 how come an MLP beats a GNN?!! 9:06 the expressive power of GNNs 10:18 rule number 1 for using GNNs 10:33 importing CORA dataset 11:28 results summary 11:51 final remarks ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #graphneuralnetwork #GATConv #pytorch #graph #convolution #GNN #GCN #pytorch #pytorchgeometric #GCNConv #DeepLearningTutorial #MachineLearningProject #AIResearch #CodingTutorial