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cs.LG2026
Innovation Capacity of Dynamical Learning Systems
Anthony M. Polloreno
In noisy physical reservoirs, the classical information-processing capacity quantifies how well a linear readout can realize tasks measurable from the input histo…
cs.LG2023★ 2 cited
Restrictions on Physical Stochastic Reservoir Computers
Anthony M. Polloreno
Reservoir computation is a recurrent framework for learning and predicting time series data, that benefits from extremely simple training and interpretability, often as the the dyn…
cs.LG2023
A Note on Noisy Reservoir Computation
Anthony M. Polloreno, Reuben R. W. Wang, Nikolas A. Tezak
In this note we extend the definition of the Information Processing Capacity (IPC) by Dambre et al [1] to include the effects of stochastic reservoir dynamics. We quantify the degr…