A Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.
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Updated
Jul 17, 2024 - Python
A Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.
Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.
An easy-to-use independent machine learning library for .net. It offers MLP models (including deep RVFL aka ELM) for common ML tasks as well as Reservoir Computer for efficiently solving ML tasks on time series data.
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/
Implementation of Echo State Networks (ESN) with experiments on MNIST and ECG5000. Includes comparison with Linear Regression and analysis of weight initialization methods for time-series and classification tasks.
Reservoir computing with coupled genetic oscillators for arrhythmia classification
Controlling computational chaotic model of heart arrhythmia using state-delayed echo state network controller. Three reservoir designs implemented.
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