DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling

7 Jun 2020Moshe EliasofEran Treister

Graph Convolutional Networks (GCNs) have shown to be effective in handling unordered data like point cloud and meshes. In this work we propose novel approaches for graph convolution, pooling and unpooling, taking inspiration from finite-elements and algebraic multigrid frameworks... (read more)

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