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"

Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Hierarchical Inter-Message Passing for Learning on Molecular Graphs

Code for "Understanding Pooling in Graph Neural Networks" (TNNLS 2022).

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…

Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

Code and dataset to test empirically the expressive power of graph pooling operators.

Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)

Pytorch and Tensorflow implementation of TVGNN, presented at ICML 2023.

Software implementation of Pyramidal Reservoir Graph Neural Networks

[IJCNN 2021] Structure-Aware Hierarchical Graph Pooling using Information Bottleneck

Self-Attention Graph Pooling [ICML-2019]

Implementation of Graph pooling and clustering operation using Graph Neural Networks in PyTorch

A repo for baseline of graph pooling.

Using Graph Attention NN for image embedding and classification

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations [AAAI-2020]

Papers on Graph Pooling for GNN and their bioinformatics application