Metadata-Version: 2.1
Name: graphesn
Version: 0.2.2
Summary: Python implementation of Deep Graph Echo State Networks
Home-page: https://github.com/dtortorella/graph-esn
Author: Domenico Tortorella, Danilo Numeroso, Alessio Gravina
Author-email: d.tortorella@phd.unipi.it, d.numeroso@phd.unipi.it, a.gravina@phd.unipi.it
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/dtortorella/graph-esn
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# Graph ESN library
Pytorch implementation of echo state networks for static graphs, temporal graphs, and dynamic graphs.

## Installation
``` python -m pip install graphesn ```

## References
* C. Gallicchio, A. Micheli (2010). Graph Echo State Networks. The 2010 International Joint Conference on Neural Networks (IJCNN 2010), pp. 3967–3974.
* C. Gallicchio, A. Micheli (2020). Fast and Deep Graph Neural Networks. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20).
* C. Gallicchio, A. Micheli (2020). Ring Reservoir Neural Networks for Graphs. The 2020 International Joint Conference on Neural Networks (IJCNN 2020).
* D. Tortorella, A. Micheli (2021). Dynamic Graph Echo State Networks. Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021), pp. 99–104.


