116 Open source projects that are alternatives of or similar to SuperGAT

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Graph Neural Networks with Keras and Tensorflow 2.

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Demo of RouteNet in ACM SIGCOMM'19

Inductive relation prediction by subgraph reasoning, ICML'20

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

The official code and datasets for "Zero-Shot Multi-View Indoor Localization via Graph Location Networks" (ACMMM 2020)

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

links to conference publications in graph-based deep learning

Code and resources on scalable and efficient Graph Neural Networks

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

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

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

odr.chalmers.se/handle/20.500.12380/256629?locale=en

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

A distributed graph deep learning framework.

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

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

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

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

Subgraph Neural Networks (NeurIPS 2020)

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

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

Visualization tool for Graph Neural Networks

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.

Summary of social recommendation papers and codes

Smart contract vulnerability detection using graph neural network (DR-GCN).

source code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)

Code and dataset of ACL2019 Paper: Graph Neural Networks with Generated Parameters for Relation Extraction.

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Awesome Graph Self-Supervised Learning

Disentagnled Graph Collaborative Filtering, SIGIR2020

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

毕业设计：基于图神经网络的异构图表示学习和推荐算法研究

Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net, Mixhop

StellarGraph - Machine Learning on Graphs

An index of recommendation algorithms that are based on Graph Neural Networks.

Graph Neural Network Library for PyTorch

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

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

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Implementation of Directional Graph Networks in PyTorch and DGL

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

Implementation of "Overlapping Community Detection with Graph Neural Networks"

Pytorch differentiable molecular dynamics

Graph-based Deep Q Network for Web Navigation

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

Combining relational context and relational paths for knowledge graph completion

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Reimplementation of Graph Embedding methods by Pytorch.

AAAI'21: Data Augmentation for Graph Neural Networks

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.