AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
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Updated
Jun 21, 2020 - Python
AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Hierarchical Graph Pooling with Structure Learning
Using Graph Attention NN for image embedding and classification
Hierarchical Inter-Message Passing for Learning on Molecular Graphs
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
Code for "Understanding Pooling in Graph Neural Networks" (TNNLS 2022).
Software implementation of Pyramidal Reservoir Graph Neural Networks
Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)
A repo for baseline of graph pooling.
Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"
Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
Implementation of Graph pooling and clustering operation using Graph Neural Networks in PyTorch
Code and dataset to test empirically the expressive power of graph pooling operators.
HiCAP---Hierarchical Clustering-based Attention Pooling for Graph Representation Learning
Pytorch and Tensorflow implementation of TVGNN, presented at ICML 2023.
Self-Attention Graph Pooling [ICML-2019]
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations [AAAI-2020]
Multi-hop Attention-based Graph Pooling: A Personalized PageRank Perspective
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