Hierarchical Graph Pooling with Structure Learning
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Updated
Jul 12, 2021 - Python
Hierarchical Graph Pooling with Structure Learning
Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"
AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph representation learning, graph regression and graph classification to join this project as contribut…
Code for "Understanding Pooling in Graph Neural Networks" (TNNLS 2022).
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
Hierarchical Inter-Message Passing for Learning on Molecular Graphs
[IJCNN 2021] Structure-Aware Hierarchical Graph Pooling using Information Bottleneck
Pytorch and Tensorflow implementation of TVGNN, presented at ICML 2023.
Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)
Self-Attention Graph Pooling [ICML-2019]
A repo for baseline of graph pooling.
Papers on Graph Pooling for GNN and their bioinformatics application
Multi-hop Attention-based Graph Pooling: A Personalized PageRank Perspective
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations [AAAI-2020]
Software implementation of Pyramidal Reservoir Graph Neural Networks
Code and dataset to test empirically the expressive power of graph pooling operators.
Using Graph Attention NN for image embedding and classification
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