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- Results on transductive/inductive benchmarks
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Classroom Contents
Graph Attention Networks - GNN Paper Explained
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- 1 - A note on geometric deep learning
- 2 - Graph theory basics
- 3 - Intro to GATs related work
- 4 - A detailed explanation of the method
- 5 - A multi-head version of the GAT
- 6 - Visualizations, spatial pooling, GNN depth
- 7 - A recap of GAT properties
- 8 - Receptive field of spatial GNNs
- 9 - Datasets, transductive vs inductive learning
- 10 - Results on transductive/inductive benchmarks
- 11 - Representations visualization t-SNE