dgl.nn (MXNet)ΒΆ
Conv LayersΒΆ
Dense Conv LayersΒΆ
Graph Convolutional layer from Semi-Supervised Classification with Graph Convolutional Networks |
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GraphSAGE layer from Inductive Representation Learning on Large Graphs |
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Chebyshev Spectral Graph Convolution layer from Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering |
Global Pooling LayersΒΆ
Apply sum pooling over the nodes in the graph. |
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Apply average pooling over the nodes in the graph. |
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Apply max pooling over the nodes in the graph. |
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Pooling layer from An End-to-End Deep Learning Architecture for Graph Classification |
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Global Attention Pooling layer from Gated Graph Sequence Neural Networks |
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Set2Set operator from Order Matters: Sequence to sequence for sets |
Heterogeneous Learning ModulesΒΆ
A generic module for computing convolution on heterogeneous graphs |
Utility ModulesΒΆ
A squential container for stacking graph neural network blocks |