#Graph-convolutional-networks
Showing 29 of 29 repositories tagged #graph-convolutional-networks, ranked by stars
Graph Neural Network Library for PyTorch
links to conference publications in graph-based deep learning
StellarGraph - Machine Learning on Graphs
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
A distributed graph deep learning framework.
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
Graph Convolutional Networks for Text Classification. AAAI 2019
🟠 A study guide to learn about Graph Neural Networks (GNNs)
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020
A Deep Graph-based Toolbox for Fraud Detection
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry
ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks
TypeDB-ML is the Machine Learning integrations library for TypeDB
Free hands-on course about Graph Neural Networks using PyTorch Geometric.
Low-Level Graph Neural Network Operators for PyG
Representation learning on large graphs using stochastic graph convolutions.
Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation, AAAI 2020
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
PyTorch implementation of our graph convolutional network (GCN) for human motion generation from music. Also with paired dance-music data for training!
Graph Convolutional Networks for 4-class EEG Classification
Unsupervised learning of atomic scale dynamics from molecular dynamics.
codes of Deep Spatio-Temporal Graph Convolutional Network for Traffic Accident Prediction
BayesGrad: Explaining Predictions of Graph Convolutional Networks
A tool for spatially-aware molecule design and optimisation via Equivariant Diffusion and GCN