Popular GitHub Repositories for Graph Attention Networks

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

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

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

resources for graph convolutional networks （图卷积神经网络相关资源）

Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)

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).

Free hands-on course about Graph Neural Networks using PyTorch Geometric.

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

A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!

ECML 2019: Graph Neural Networks for Multi-Label Classification

PyTorch code for ICPR 2020 paper "DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting"

GraphCON (ICML 2022)

Anti Money Laundering Detection using Graph Attention Network

PyTorch implementation of the Graph Attention Networks (GAT) based on the paper "Graph Attention Network" by Velickovic et al - https://arxiv.org/abs/1710.10903v3

[NLPCC 2020] Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks

Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction. ICML 2020 Graph Representation Learning and Beyond (GRL+) Workshop

S&P100 stocks analysis via Graph Neural Networks (Forecasting, Clustering, Trend classification, Stocks ranking for optimal stock picking)

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

Text Classification using Graph Convolutional Neural Networks and Natural Language Processing Techniques

Source code for "Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation" (IJCAI 2020)