AI RESEARCH
Echo State Networks for Time Series Forecasting: Hyperparameter Sweep and Benchmarking
arXiv CS.LG
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ArXi:2602.03912v2 Announce Type: replace This paper investigates the forecasting performance of Echo State Networks (ESNs) for univariate time series forecasting using a subset of the M4 Forecasting Competition dataset. Focusing on monthly and quarterly time series with at most 20 years of historical data, we evaluate whether a fully automatic, purely feedback-driven ESN can serve as a competitive alternative to widely used statistical forecasting methods.