Graph Attention Network

Graph Attention Networks (GATs) are a type of graph neural network designed to learn relationships within graph-structured data by assigning attention weights to different nodes based on their relevance to a given task. Current research focuses on improving GAT performance in various applications, including developing more sophisticated attention mechanisms, addressing limitations in handling heterophilic graphs and long-range dependencies, and integrating GATs with other techniques like transformers and multi-modal data fusion. This work has significant implications across diverse fields, enabling advancements in areas such as drug discovery, financial modeling, image analysis, and social network analysis through improved data representation and predictive modeling.

Papers

July 18, 2023

Pixel-wise Graph Attention Networks for Person Re-identification
Wenyu Zhang, Qing Ding, Jian Hu, Yi Ma, Mingzhe Lu
Convolutional Neural Network Graph Convolutional Network Graph Attention Network

July 12, 2023

Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events
Boyang Yu, Nikolai Hartmann, Luca Schinnerl, Thomas Kuhr
Neural Network Graph Attention Network Graph Attention Event Description Detector Simulation Background Suppression Reference Signal Received Power

July 11, 2023

Supervised Attention Using Homophily in Graph Neural Networks
Michail Chatzianastasis, Giannis Nikolentzos, Michalis Vazirgiannis
Graph Neural Network Attention Mechanism Graph Attention Network Node Representation Graph Attention Supervised Attention Node Classification Datasets

June 27, 2023

SENSEi: Input-Sensitive Compilation for Accelerating GNNs
Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis, Serif Yesil, Josep Torrellas, Charith Mendis
Graph Neural Network Graph Attention Network GNN Model GNN Based Service Sparse Matrix Multiplication Efficient Compilation GNN Computation

June 20, 2023

Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method
Shuo Han, Jiacheng Liu, Jiayun Wu, Yinan Chen, Li Tao
Transformer Based Graph Representation Learning Graph Transformer Graph Attention Network Graph Attention Graph Clustering Graph Auto Efficient Graph Graph Transformation

May 30, 2023

FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design
Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu, Qing Li
Graph Attention Network Nearest Neighbor Failure Analysis Robust Network Traffic Engineering

May 25, 2023

May 12, 2023

Fisher Information Embedding for Node and Graph Learning
Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt
Graph Learning Graph Attention Network Graph Attention Fisher Information Attention Graph Attention Based Graph Neural Network

May 9, 2023

Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction
Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang
Graph Attention Network Heterogeneous Graph Neural Network Financial Time Series Stock Movement Prediction Relation Graph

April 21, 2023

April 7, 2023

BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection
Yalu Wang, Zhijie Han, Jie Li, Xin He
Graph Neural Network Graph Attention Network Intrusion Detection Network Intrusion Detection Behavioral Similarity

March 29, 2023

Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution
Rui Luo, Vikram Krishnamurthy
Graph Attention Network Sport Analytics Temporal Convolution Player Performance Sport Data Player Interaction

March 27, 2023

Knowledge Enhanced Graph Neural Networks for Graph Completion
Luisa Werner, Nabil Layaïda, Pierre Genevès, Sarah Chlyah
Graph Attention Network Graph Completion

March 26, 2023

FairGAT: Fairness-aware Graph Attention Networks
O. Deniz Kose, Yanning Shen
Graph Neural Network Graph Attention Network Group Fairness Algorithmic Bias Fairness Assessment

March 25, 2023

Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA)
U. Nazir, W. Islam, M. Taj
Neural Network Graph Attention Network Satellite Imagery Adjacency Matrix Spatio Temporal Learning

Graph Attention Network

Papers

Pixel-wise Graph Attention Networks for Person Re-identification

Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events

Supervised Attention Using Homophily in Graph Neural Networks

SENSEi: Input-Sensitive Compilation for Accelerating GNNs

Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method

FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design

Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications

Demystifying Oversmoothing in Attention-Based Graph Neural Networks

Syntactic Knowledge via Graph Attention with BERT in Machine Translation

GATology for Linguistics: What Syntactic Dependencies It Knows

Distributed Learning over Networks with Graph-Attention-Based Personalization

Fisher Information Embedding for Node and Graph Learning

Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction

Gradient Derivation for Learnable Parameters in Graph Attention Networks

TC-GAT: Graph Attention Network for Temporal Causality Discovery

BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection

Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution

Knowledge Enhanced Graph Neural Networks for Graph Completion

FairGAT: Fairness-aware Graph Attention Networks

Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA)