nlin.CD · 2026-08-03 · No. 73

Chaotic Dynamics, 2026-08-03.

1 new papers in nlin.CD. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Extrapolating the emergence of Hamiltonian chaos with random-feature Hamiltonian neural networks

    Jaesung Choi

    nlin.CD · cs.LG · physics.comp-ph

    Machine learning of Hamiltonian dynamics has driven growing interest in Hamiltonian neural networks (HNNs), which encode Hamilton's equations of motion into the learning architecture. Despite this progress, it remains unknown whether such networks can predict dynamical regimes absent from their training data, in particular the broad chaotic sea that emerges beyond the observed parameter interval. We address this question using a...

    arxiv.org/abs/2607.28977 · PDF

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