#

graph-attention-network

Here are 29 public repositories matching this topic...

pytorch-GAT

gordicaleksa / pytorch-GAT

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!

python deep-learning jupyter pytorch attention attention-mechanism graph-attention-networks self-attention pytorch-implementation gat graph-attention-network pytorch-gat gat-tutorial

Updated Nov 17, 2022
Jupyter Notebook

Jhy1993 / HAN

Heterogeneous Graph Neural Network

heterogeneous-network network-embedding graph-neural-network heterogeneous-graph graph-attention-network heterogeneous-graph-neural-network

Updated May 6, 2020
Python

IndexFziQ / GNN4NLP-Papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

natural-language-processing knowledge-graph question-answering knowledge-representation graph-convolutional-networks knowledge-based-systems paperlist paper-list graph-neural-network graph-attention-network heterogeneous-graphs

Updated May 9, 2023

thunlp / KernelGAT

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

kernel fact-verification graph-attention-network

Updated Dec 8, 2022
Python

taishan1994 / pytorch_HAN

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

heterogeneous-network network-embedding graph-neural-network heterogeneous-graph graph-attention-network heterogeneous-graph-neural-network

Updated Jan 13, 2023
Python

raunakkmr / GraphSAGE-and-GAT-for-link-prediction

GraphSAGE and GAT for link prediction.

deep-learning pytorch graphsage graph-neural-networks graph-attention-network

Updated Sep 11, 2019
Jupyter Notebook

xiaoqian19940510 / TASLP-EAREE

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

reinforcement-learning deep-learning pytorch multi-task bert self-attention graph-attention-network

Updated Oct 31, 2022
Python

raunakkmr / Graph-Attention-Networks

PyTorch implementation of Graph Attention Networks

deep-learning pytorch graph-neural-networks graph-attention-network

Updated Sep 10, 2019
Python

wzever / RGCN-GAT-Link-Prediction

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

recommender-system link-prediction heterogeneous-graph graph-attention-network dgl rgcn-architecture academic-network

Updated Jun 22, 2023
Python

double125 / Graph-Matching-Attention

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

graph visual-question-answering feature-fusion graph-attention-network graph-matcing-network cross-modality-vqa

Updated Feb 16, 2023
Python

taishan1994 / pytorch_gat

Pytorch implementation of graph attention network

tensorflow pytorch gat deeplearn graph-attention-network

Updated Feb 23, 2023
Python

gat-or

njmarko / gat-or

GATor is a Graph Attention Network for object detection with relational reasoning

graph faster-rcnn object-detection graph-neural-networks graph-attention-network

Updated Jan 25, 2022
Jupyter Notebook

ShuvozitGhose / Ground-Terrain-EoT

Modeling Extent-of-Texture Information for Ground Terrain Recognition

pytorch deeplearning graph-attention-network ground-terrain-recognition extent-of-texture-modeling

Updated Apr 25, 2020
Python

withai / Docked-protein-Interaction-ranking-using-graph-neural-networks

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

pytorch neural-networks protein-interaction graph-neural-networks graph-convolutional-neural-networks graph-attention-network protein-interaction-ranking

Updated Aug 26, 2020
Python

YeskendirK / Reducing-Oversmoothing

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

graph-algorithms graph-neural-networks graph-attention-network oversmoothing

Updated Jan 8, 2023
Python

bmezaris / Gated-ViGAT

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.

video deep-learning gating explainable-ai explainability attention-network graph-attention-network video-event-recognition frame-selection-policy

Updated Mar 3, 2023
Python

khanmhmdi / GAT-Graph-attention-neural-network-

This repository contain the unofficial implementation of the graph attention neural network.

deep-learning neural-network graph neural-networks attention-mechanism attention-is-all-you-need graph-neural-networks gat graph-neural-network graph-attention-network

Updated Jan 2, 2023

dice-group / GATES

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

ensemble-learning knowledge-graph-embeddings entity-summarization graph-attention-network text-embeddings deep-learning-on-graphs

Updated May 6, 2023
Python

animeshprasad / Glocal

Keyphrase extraction using graph convolution

graph-convolutional-networks graph-attention-network

Updated Oct 9, 2019
Python

bmezaris / ViGAT

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.

video attention-model video-events explainable-ai event-recognition graph-attention-network event-explanation bottom-up-analysis

Updated Nov 11, 2022
Python

Improve this page

Add a description, image, and links to the graph-attention-network topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the graph-attention-network topic, visit your repo's landing page and select "manage topics."