A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.
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Updated
Jun 10, 2024 - Python
A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.
A simple and flexible code for Reservoir Computing architectures like Echo State Networks
An Echo State Network module for PyTorch.
Python library for Reservoir Computing using Echo State Networks
RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.
Code for Reservoir computing (Echo state network)
Machine Learning with Echo State Networks, a scikit-learn compatible package.
Nengo library of additional extensions
[Nature Machine Intelligence 2023] "Echo state graph neural networks with analogue random resistive memory arrays."
Echo state network framework, NARMA10 dataset generator as an demonstration supplied.
An organized collection of Reservoir Computing models and techniques that is well-integrated within the PyTorch API.
Continual Learning with Echo State Networks experiments
Reservoir is a Python package to train and optimize Echo State Networks
Out-of-the-box framework for Echo State Networks
Repo for EchoVPR: Echo State Networks for Visual Place Recognition
A new version of world models using Echo-state networks and random weight-fixed CNNs
Question Classification with Untrained Recurrent Embeddings
Dash App to Visualize ESN Time Series Predictions
Physics-aware machine learning with echo state networks for the prediction of chaotic systems.
In this paper, we propose the use of Echo State Networks, for anomaly detection on-the-edge in aerospace applications. The anomaly detection method uses a nonparametric dynamic threshold to detect anomalous behaviours from the observed data by comparing it to the model's predictions.
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