dhg.models
Models on Graph
The GCN model proposed in Semi-Supervised Classification with Graph Convolutional Networks paper (ICLR 2017). |
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The GraphSAGE model proposed in Inductive Representation Learning on Large Graphs paper (NIPS 2017). |
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The GAT model proposed in Graph Attention Networks paper (ICLR 2018). |
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The GIN model proposed in How Powerful are Graph Neural Networks? paper (ICLR 2019). |
Models on Bipartite Graph
The NGCF model proposed in Neural Graph Collaborative Filtering paper (SIGIR 2019). |
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The LightGCN model proposed in LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation paper (SIGIR 2020). |
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The BGNN-Adv model proposed in Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs paper (TNNLS 2020). |
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The BGNN-MLP model proposed in Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs paper (TNNLS 2020). |
Models on Hypergraph
The HGNN model proposed in Hypergraph Neural Networks paper (AAAI 2019). |
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The HGNN + model proposed in HGNN+: General Hypergraph Neural Networks paper (IEEE T-PAMI 2022). |
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The HyperGCN model proposed in HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs paper (NeurIPS 2019). |
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The DHCF model proposed in Dual Channel Hypergraph Collaborative Filtering paper (KDD 2020). |
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The HNHN model proposed in HNHN: Hypergraph Networks with Hyperedge Neurons paper (ICML 2020). |
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The UniGCN model proposed in UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks paper (IJCAI 2021). |
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The UniGAT model proposed in UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks paper (IJCAI 2021). |
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The UniSAGE model proposed in UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks paper (IJCAI 2021). |
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The UniGIN model proposed in UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks paper (IJCAI 2021). |