Web Reference: Sep 23, 2025 · The basic framework is introduced for scalar-valued learning and then extended to operator learning. Finally, learning dynamical systems is formulated as a suitable operator learning problem, leveraging Koopman operator theory. This expository article presents the approach to statistical machine learning based on reproducing kernel Hilbert spaces. The basic framework is introduced for scalar-valued learning and then extended to operator learning. Operator learning aims to discover properties of an underlying dynamical system or partial differential equation (PDE) from data. Here, we present a step-by-step guide to operator learning.
YouTube Excerpt: Speaker: Lorenzo ROSASCO (University Of Genova, Italy) Spring College on the Physics of Complex Systems | (smr 3921)
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