Simple modular python package for physical reservoir computing. Use your own experimental data.
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Updated
Sep 9, 2024 - Python
Simple modular python package for physical reservoir computing. Use your own experimental data.
A simple and flexible code for Reservoir Computing architectures like Echo State Networks
PyPi Package of Self-Organizing Recurrent Neural Networks (SORN) and Neuro-robotics using OpenAI Gym
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.
Official repository for the paper "Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings" (NeurIPS 2023)
A Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.
Reservoir Computing for Chaotic Time Series Prediction
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Criticality analysis on complex networks using Power-law scaling functions, exponential relations, and phase transitions
This repository has implementations of various alternatives to backpropagation for training neural networks.
EvoDynamic seeks to evolve and develop suitable discrete dynamic models of self-organizing systems based on local interactions.
Out-of-the-box framework for Echo State Networks
speed up the calculation of the output matrix
RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.
Machine Learning with Echo State Networks, a scikit-learn compatible package.
turbESN is an echo state network implementation, used in my PhD research as part of the DeepTurb project of the Carl-Zeiss Stiftung. See https://pypi.org/project/turbESN/
An Echo State Network module for PyTorch.
An organized collection of Reservoir Computing models and techniques that is well-integrated within the PyTorch API.
Question Classification with Untrained Recurrent Embeddings
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