arXiv Machine Learning July 21, 2026 By Charles Bokor, Mark Cary, Denise Morrey, Fabrizio Bonatesta

fSRD: Fuzzy Spectral Region Decomposition -- Automated Multi Operator Koopman Representations via an Adaptive Spectral Learning Architecture

Read the original on arXiv Machine Learning →

arXiv:2607. 17990v1 Announce Type: new Abstract: Highly nonlinear chaotic dynamical systems remain difficult to model due to fundamental trade-offs between complexity, expressivity, and data efficiency.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Jun 4

Deep Embedded Multiplicative DMD for Algebra-Preserving Koopman Learning

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arXiv Machine Learning

Jun 24

Adversarial dynamical systems characterize when data-driven learning succeeds or fails

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arXiv AI

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Eigenanalysis framework for autoregressive neural emulators of multi-scale chaotic dynamics

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arXiv AI

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arXiv AI

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arXiv Machine Learning

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Spectral Distillation: From Nonlinear Dynamics to Linear State-Space Models

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By Liane Galanti, Devan Shah, Shlomo Fortgang, Elad Hazan

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