Heterogeneous Graph Neural Network

The source codes for Fine-grained Fact Verification with Kernel Graph Attention Network.

异构图神经网络HAN。Heterogeneous Graph Attention Network (HAN) with pytorch

The GitHub repository for the paper "Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations"

PyTorch implementation of Graph Attention Networks

Course project of SJTU CS3319: Foundations of Data Science, 2023 spring

Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering

Pytorch implementation of graph attention network

Modeling Extent-of-Texture Information for Ground Terrain Recognition

A deep learning library to rank protein complexes using graph neural networks

Source code accompanying the paper "Reducing Over-smoothing in Graph Neural Networks Using Relational Embeddings" published in DLG-AAAI’23

Gated-ViGAT. Code and data for our paper: N. Gkalelis, D. Daskalakis, V. Mezaris, "Gated-ViGAT: Efficient bottom-up event recognition and explanation using a new frame selection policy and gating mechanism", IEEE International Symposium on Multimedia (ISM), Naples, Italy, Dec. 2022.

Graph Attention Networks for Entity Summarization is the model that applies deep learning on graphs and ensemble learning on entity summarization tasks.

Keyphrase extraction using graph convolution

This repository hosts the scripts and some of the pre-trained models presented in out paper "ViGAT: Bottom-up event recognition and explanation in video using factorized graph attention network", IEEE Access, 2022.

IDPS-ESCAPE (Intrusion Detection and Prevention Systems for Evading Supply Chain Attacks and Post-compromise Effects), part of the CyFORT project: open-source SOAR system powered by a dedicated ML-based anomaly detection toolbox (ADBox) integrated with open-source software such as Wazuh and Suricata.

Detecting Hallucinations in Large Language Model Generations using Graph Structures

Implementation of the spatialGAT in the paper: Spatial Attention Based Grid Representation Learning for Predicting Origin–Destination Flow (IEEE Big Data 2022)

A Drug Metabolite & Toxicity Property Predictor Based on Graph Neural Network

Dense and Sparse Implementation of GAT written by PyTorch