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Found 4 papers, 0 papers with code
Improving the Performance of Echo State Networks Through Feedback
In this paper, we demonstrate that by feeding some component of the reservoir state back into the network through the input, we can drastically improve upon the performance of a given ESN.
A Small-Gain Theorem for Discrete-Time Convergent Systems and Its Applications
Convergent, contractive or incremental stability properties of nonlinear systems have attracted interest for control tasks such as observer design, output regulation and synchronization.
Temporal Information Processing on Noisy Quantum Computers
The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems.
Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems
In this paper, we develop a theory of learning nonlinear input-output maps with fading memory by dissipative quantum systems, as a quantum counterpart of the theory of approximating such maps using classical dynamical systems.
