LRGA

KO | EN

gitlite — search

#python #hacktoberfest #golang #rust #docker #macos #windows #vue #awesome-list #pytorch #ios #mcp #openai #open-source

(★ 12)

Low Rank Global Attention for Graph Neural Networks

LRGA 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# LRGA - Low Rank Global Attention

This repository contains an implementation to the paper: "From Graph Low-Rank Global Attention to 2-FWL Approximation".

LRGA is a Low Rank Global Attention module for Graph Neural Networks. Our method implements an efficient and scalable global attention, taking advantage of the efficiency of low rank matrix-vector multiplication. From a practical point of view, augmenting existing GNN layers with LRGA produces state of the art results.

For more details:

paper: https://arxiv.org/abs/2006.07846.

video: https://www.youtube.com/watch?v=ZDAyG48B-LA&t=2s.

## Installation Requirmenets
Follow the installation instructions specified here - https://github.com/snap-stanford/ogb.

## Usage
To run the code over examples from the OGB benchmark, go to the linkpropprod directory
and follow the README file in that folder.

## Citation
    @misc{puny2020graph,
        title={From Graph Low-Rank Global Attention to 2-FWL Approximation},
        author={Omri Puny and Heli Ben-Hamu and Yaron Lipman},
        year={2020},
        eprint={2006.07846},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }

LRGA

LRGA 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

LRGA

LRGA 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README