graph-pooling

Hierarchical Graph Pooling with Structure Learning

Reproduces the results of MinCutPool 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)

Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".

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 presented as presented at NeurIPS 2023

A biologically interpretable graph neural network for multistain computational pathology - CVPR 2025

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

Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.

Implementation of the BNPool layer and code to reproduce the experiments in "Bayesian Nonparametric GNNs for graph pooling and clustering".

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

Official repository of the paper "Pyramidal Reservoir Graph Neural Networks".

Self-Attention Graph Pooling [ICML-2019]

Official repository of the paper "MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks" presented at ICLR 2025.

Papers on Graph Pooling for GNN and their bioinformatics application