#Graph-neural-networks
Showing 60 of 113 repositories tagged #graph-neural-networks, ranked by stars
Graph Neural Network Library for PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!
links to conference publications in graph-based deep learning
A unified, comprehensive and efficient recommendation library
RuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
๐จ ๐ ๐ป ๐ GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | ไธ็ซๅผๅพ่ฎก็ฎ็ณป็ป
StellarGraph - Machine Learning on Graphs
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
A distributed graph deep learning framework.
Repository for benchmarking graph neural networks (JMLR 2023)
Graph Neural Networks with Keras and Tensorflow 2.
Benchmark datasets, data loaders, and evaluators for graph machine learning
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
๐ An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
A powerful and flexible machine learning platform for drug discovery
A Python Library for Graph Outlier Detection (Anomaly Detection)
A Graph Neural Network Library in Jax
Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
๐ A study guide to learn about Graph Neural Networks (GNNs)
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
Protein Graph Library
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Papers about graph transformers.
Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
A pytorch library for graph and hypergraph computation.
[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"
Papers about explainability of GNNs
Python package for graph neural networks in chemistry and biology
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
A Deep Graph-based Toolbox for Fraud Detection
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
Colab Notebooks covering deep learning tools for biomolecular structure prediction and design
Joint Deep Matcher for Points and Lines ๐ผ๏ธ๐ฅ๐ผ๏ธ (ICCV 2023)
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
A python library for social event detection
GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
Python library assists deep learning on graphs
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
Deep and conventional community detection related papers, implementations, datasets, and tools.
[ECCV2020 Oral] Learning Lane Graph Representations for Motion Forecasting
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
A Euclidean diffusion model for structure-based drug design.
Free hands-on course about Graph Neural Networks using PyTorch Geometric.
Pytorch Library for Relational Table Learning with LLMs.
DANCE: a deep learning library and benchmark platform for single-cell analysis
tsl: a PyTorch library for processing spatiotemporal data.
A list of awesome GNN systems.
This is a tutorial for PyTorch Geometric on the YooChoose dataset
Segment Anything Model for large-scale, vectorized road network extraction from aerial imagery. CVPRW 2024
A batteries-included kit for knowledge graphs
A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).