https://github.com/computorg/published-202505-ferte-reservoirnet

Reservoir Computing in R: a Tutorial for Using reservoirnet to Predict Complex Time-Series
https://github.com/computorg/published-202505-ferte-reservoirnet

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Reservoir Computing in R: a Tutorial for Using reservoirnet to Predict Complex Time-Series

• Host: GitHub
• URL: https://github.com/computorg/published-202505-ferte-reservoirnet
• Owner: computorg
• License: cc-by-4.0
• Created: 2025-05-26T09:18:59.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-07-29T07:49:18.000Z (11 months ago)
• Last Synced: 2025-07-29T09:43:36.871Z (11 months ago)
• Language: TeX
• Homepage: http://computo-journal.org/published-202505-ferte-reservoirnet/
• Size: 20.6 MB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Reservoir Computing in R: a Tutorial for Using reservoirnet to Predict Complex Time-Series

Thomas Ferté, Kalidou Ba, Dan Dutartre, Pierrick Legrand, Vianney

Jouhet, Rodolphe Thiébaut, Xavier Hinaut, Boris P Hejblum

2025-06-27

### Citation

Thomas Ferté, Kalidou Ba, Dan Dutartre, Pierrick Legrand, Vianney Jouhet, Rodolphe Thiébaut, Xavier Hinaut and Boris P Hejblum (June 2025). Reservoir Computing in R: a Tutorial for Using reservoirnet to Predict Complex Time-Series. Computo.

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### Authors’ affiliations

- Thomas Ferté (Inserm, Inria, CHU de Bordeaux)

- Kalidou Ba (Inserm, Inria)

- Dan Dutartre (Inria)

- Pierrick Legrand (Bordeaux INP, Inria, IMS)

- Vianney Jouhet (Inserm, CHU de Bordeaux)

- Rodolphe Thiébaut (Inserm, Inria, CHU de Bordeaux)

- Xavier Hinaut (Inria, IMN, LaBRI)

- Boris P Hejblum (Inserm, Inria)

### Abstract

Reservoir Computing (RC) is a machine learning method based on neural

networks that efficiently process information generated by dynamical

systems. It has been successful in solving various tasks including time

series forecasting, language processing or voice processing. RC is

implemented in `Python` and `Julia` but not in `R`. This article

introduces `reservoirnet`, an `R` package providing access to the

`Python` API `ReservoirPy`, allowing `R` users to harness the power of

reservoir computing. This article provides an introduction to the

fundamentals of RC and showcases its real-world applicability through

three distinct sections. First, we cover the foundational concepts of

RC, setting the stage for understanding its capabilities. Next, we delve

into the practical usage of `reservoirnet` through two illustrative

examples. These examples demonstrate how it can be applied to real-world

problems, specifically, regression of COVID-19 hospitalizations and

classification of Japanese vowels. Finally, we present a comprehensive

analysis of a real-world application of `reservoirnet`, where it was

used to forecast COVID-19 hospitalizations at Bordeaux University

Hospital using public data and electronic health records.