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mdgcn

Multiscale Dynamic Graph Convolutional Network for hyperspectral image classification

mixhop-and-n-gcn

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

mnist-superpixel

MWP for superpixel GNN classification

mnistgnn

MNIST classification by using GCN

musae

The reference implementation of "Multi-scale Attributed Node Embedding".

mushroom-graph-clustering

Spectral graph clustering of a dataset of mushrooms

must-read-papers-and-continuous-tracking-on-graph-neural-network-gnn-progress

Papers on Graph neural network(GNN)

mvsc

Implementation of 'Large-Scale Multi-View Spectral Clustering via Bipartite Graph'

neutrongnn

Graph neural net for neutron captures

nvgraph

objectdetection

Object detection using semantic segmentation

ogb

Benchmark datasets, data loaders, and evaluators for graph machine learning

ohmnet

OhmNet: Representation learning in multi-layer graphs

onespectralclustering

Graph-based clustering using the inverse power method for nonlinear eigenproblems

paper-cnn-graph-nips2016

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

paper-cnn-graph-recurrent-iclr2017

Structured Sequence Modeling with Graph Convolutional Recurrent Networks

patch_graph_object_detection

Experiments to use graphs with spacial and similarity relationships of image features for object detection

patchycapsules

pgmexplainer

Generating PGM Explanation for GNN predictions

planetoid

Semi-supervised learning with graph embeddings

powerful-gnns

How Powerful are Graph Neural Networks?

pretrain-gnns

Strategies for Pre-training Graph Neural Networks

pspectralclustering

Spectral Clustering based on the graph p-Laplacian

pygat

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

pygcn

Graph Convolutional Networks in PyTorch

pygkernels

Graphs clustering using kernel measures and estimators. Kernel KMeans, Spectral Clustering, Kernel Ward etc.

pygsp_tutorial_graphsip

Graph signal processing tutorial, presented at the GraphSiP summer school.

pyhgt

Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric

pynetmelt

Integration of networks to enhance semi-supervised learning algorithms over graphs.

pytorch-biggraph

Generate embeddings from large-scale graph-structured data.