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Forecasting, filtering, and reconstruction of stochastic stationary signals using discrete-time reservoir computers., , and . CoRR, (2015)Reservoir Computing: Information Processing of Stationary Signals., , and . CSE/EUC/DCABES, page 496-503. IEEE Computer Society, (2016)Estimation and empirical performance of non-scalar dynamic conditional correlation models., , and . Comput. Stat. Data Anal., (2016)Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems., and . J. Mach. Learn. Res., (2018)Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals., , , and . Neural Comput., 28 (7): 1411-1451 (2016)Infinite-dimensional reservoir computing., , and . CoRR, (2023)Risk bounds for reservoir computing., , and . CoRR, (2019)Nonlinear memory capacity of parallel time-delay reservoir computers in the processing of multidimensional signals., , , and . CoRR, (2015)Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems., and . CoRR, (2017)Echo state networks are universal., and . Neural Networks, (2018)