Top 99 graph-neural-networks open source projects

A distributed graph deep learning framework.

StellarGraph - Machine Learning on Graphs

Graph Neural Networks with Keras and Tensorflow 2.

Graph Neural Network Library for PyTorch

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Python package built to ease deep learning on graph, on top of existing DL frameworks.

links to conference publications in graph-based deep learning

Implementation of Directional Graph Networks in PyTorch and DGL

Summary of open source code for deep learning models in the field of traffic prediction

Implementation of "Overlapping Community Detection with Graph Neural Networks"

Inductive relation prediction by subgraph reasoning, ICML'20

Graph-based Deep Q Network for Web Navigation

Source code and datasets for ACL 2020 paper: Neighborhood Matching Network for Entity Alignment.

Combining relational context and relational paths for knowledge graph completion

Code for NAACL 2021 paper: MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences

A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.

Implement of DiGCN, NeurIPS-2020

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

No description or website provided.

Combining relational context and relational paths for knowledge graph completion

⌛ Introducing Self-Attention to Target Attentive Graph Neural Networks (AISP '22)

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).

A reading list for deep graph learning acceleration.

Code & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"

[COLING 2020] Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis

A spherical convolutional neural network for cosmology (TFv1).

Papers about explainability of GNNs

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

This is a paper list about Resource Allocation in Network Functions Virtualization (NFV) and Software-Defined Networking (SDN).

Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)

Smart Contract Vulnerability Detection Using Graph Neural Networks (IJCAI-20 Accepted)

Supervised community detection with line graph neural networks

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

This is a Pytorch implementation of GraphLIME

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Representing Long-Range Context for Graph Neural Networks with Global Attention

[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

Geometric Deep Learning for Flux

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

Probabilistic Type Inference using Graph Neural Networks

Graph-based machine learning for chemical property prediction

Representation Learning on Graphs with Jumping Knowledge Networks

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Message Passing Neural Networks for Simplicial and Cell Complexes

A curated list of awesome graph & self-supervised-learning-based recommendation.

Locally Private Graph Neural Networks (ACM CCS 2021)

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

Tutorials for Machine Learning on Graphs