https://github.com/MKLab-ITI/JGNN

A Fast Graph Neural Network Library written in Native Java
https://github.com/MKLab-ITI/JGNN

Last synced: 25 days ago
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A Fast Graph Neural Network Library written in Native Java

• Host: GitHub
• URL: https://github.com/MKLab-ITI/JGNN
• Owner: MKLab-ITI
• License: apache-2.0
• Created: 2020-11-26T17:48:57.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2025-03-23T23:21:12.000Z (over 1 year ago)
• Last Synced: 2026-01-31T09:13:58.298Z (5 months ago)
• Language: Java
• Size: 19.4 MB
• Stars: 22
• Watchers: 4
• Forks: 5
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-java - JGNN

README

          
# JGNN 

[![Latest nightly release](https://jitpack.io/v/MKLab-ITI/JGNN.svg)](https://jitpack.io/#MKLab-ITI/JGNN) [![Latest stable release](https://img.shields.io/badge/JAR-1.3.40%20stable-red)](https://github.com/MKLab-ITI/JGNN/releases/latest) 

*Resource efficient machine learning and graph neural networks in native Java.*

Graph Neural Networks (GNNs) are getting more and more popular, for example to

make predictions based on relational information, or to perform inference

on small datasets. JGNN provides native Java implementations of this machine

learning paradigm, and does not require dedicated hardware or firmware.

Follow the Jitpack badge for Gradle or Maven integration.

* Cross-platform

* Lightweight

* Optimized: data views, automatic datatypes, SIMD, parallelized batching

* Neuralang scripting language for model definitions

Feel free to contribute in any way, for example through the [issue tracker](https://github.com/MKLab-ITI/JGNN/issues). In addition to bug reports, 

requests for features and clarifications are welcome.

## :rocket: [Guidebook](https://mklab-iti.github.io/JGNN/)

## :dart: [Javadoc](https://mklab-iti.github.io/JGNN/javadoc/)

## :computer: [Tutorials](tutorials/README.md)

## :notebook: Citation

```

@article{krasanakis2023101459,

	title = {JGNN: Graph Neural Networks on native Java},

	journal = {SoftwareX},

	volume = {23},

	pages = {101459},

	year = {2023},

	issn = {2352-7110},

	doi = {https://doi.org/10.1016/j.softx.2023.101459},

	url = {https://www.sciencedirect.com/science/article/pii/S2352711023001553},

	author = {Emmanouil Krasanakis and Symeon Papadopoulos and Ioannis Kompatsiaris}

}

```

**Apache license 2.0. Copyright © 2024, Emmanouil Krasanakis (maniospas@hotmail.com).**