Diversifying Non-dissipative Reservoir Computing Dynamics

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Preprint , Conference object 01 Jan 2023 Italy English Publisher:Springer Nature SwitzerlandFunded by:EC | TEACHING, EC | EMERGE

Authors: Gallicchio C.;

doi: 10.1007/978-3-031-44198-1_15 , 10.5281/zenodo.8233785 , 10.5281/zenodo.8233784

handle: 11568/1222210

Diversifying Non-dissipative Reservoir Computing Dynamics

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Abstract

The Euler State Network (EuSNs) model is a recently proposed Reservoir Computing methodology that provides stable and non- dissipative untrained dynamics by discretizing an appropriately con-strained ODE. In this paper, we propose alternative formulations of the reservoirs for EuSNs, aiming at improving the diversity of the resulting dynamics. Our empirical analysis points out the effectiveness of the proposed approaches on a large pool of time-series classification tasks.

This is a pre-print of a paper accepted to the ICANN 2023 conference

Country

Italy

Related Organizations

University of Pisa
Italy

Keywords

Echo State Networks; Euler State Networks; Reservoir Computing

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