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math.DS2024
Forecasting causal dynamics with universal reservoirs
Lyudmila Grigoryeva, James Louw, Juan-Pablo Ortega
An iterated multistep forecasting scheme based on recurrent neural networks (RNN) is proposed for the time series generated by causal chains with infinite memory. This forecasting…
math.DS2024
Data-driven cold starting of good reservoirs
Lyudmila Grigoryeva, Boumediene Hamzi, Felix P. Kemeth +4
Using short histories of observations from a dynamical system, a workflow for the post-training initialization of reservoir computing systems is described. This strategy is called…