Fast Graph Representation Learning with PyTorch Geometric

6 Mar 2019Matthias FeyJan Eric Lenssen

We introduce PyTorch Geometric, a library for deep learning on irregularly structured input data such as graphs, point clouds and manifolds, built upon PyTorch. In addition to general graph data structures and processing methods, it contains a variety of recently published methods from the domains of relational learning and 3D data processing... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Node Classification Citeseer APPNP Accuracy 70.0% # 17
Graph Classification COLLAB GCN Accuracy 80.6% # 4
Node Classification Cora APPNP Accuracy 82.2% # 15
Graph Classification IMDb-B GIN-0 Accuracy 72.8% # 11
Graph Classification MUTAG GIN-0 Accuracy 85.7% # 24
Graph Classification PROTEINS DiffPool Accuracy 75.1% # 25
Node Classification Pubmed APPNP Accuracy 79.4% # 11
Graph Classification REDDIT-B DiffPool Accuracy 92.1 # 2