CRAN/E | reservoirnet

reservoirnet

Reservoir Computing and Echo State Networks

Installation

About

A simple user-friendly library based on the 'python' module 'reservoirpy'. It provides a flexible interface to implement efficient Reservoir Computing (RC) architectures with a particular focus on Echo State Networks (ESN). Some of its features are: offline and online training, parallel implementation, sparse matrix computation, fast spectral initialization, advanced learning rules (e.g. Intrinsic Plasticity) etc. It also makes possible to easily create complex architectures with multiple reservoirs (e.g. deep reservoirs), readouts, and complex feedback loops. Moreover, graphical tools are included to easily explore hyperparameters. Finally, it includes several tutorials exploring time series forecasting, classification and hyperparameter tuning. For more information about 'reservoirpy', please see Trouvain et al. (2020) doi:10.1007/978-3-030-61616-8_40. This package was developed in the framework of the University of Bordeaux’s IdEx "Investments for the Future" program / RRI PHDS.

github.com/reservoirpy
System requirements Python (>= 3.7)

Key Metrics

Version 0.2.0
R ≥ 3.6
Published 2023-04-04 400 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks reservoirnet results
Language en-US

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Maintainer

Maintainer

Thomas Ferte

thomas.ferte@u-bordeaux.fr

Authors

Thomas Ferte

aut / cre / trl

Kalidou Ba

aut / trl

Nathan Trouvain

aut

Rodolphe Thiebaut

aut

Xavier Hinaut

aut

Boris Hejblum

aut / trl

Material

README
Reference manual
Package source

Vignettes

Classification with Reservoir Computing
01 - The basics first, you should learn
02 - Hyperparameter tuning with random search

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 3.6

Imports

reticulate
testthat ≥ 3.0.0
rlang
ggplot2
ggpubr
janitor
dplyr
magrittr
methods

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