math.NA · 2026-08-22 · No. 92

Numerical Analysis, 2026-08-22.

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

01 — The papers

1 entries
  1. 01

    Learning Deterministic and Stochastic Forced Hamiltonian Systems

    Benedikt Brantner, Tomasz Tyranowski

    math.NA · cs.LG · math.SG

    We develop a geometric framework for learning deterministic and stochastic forced Hamiltonian systems with neural networks. Motivated by the Lagrange-d'Alembert principle and the theory of variational integrators, we introduce the notion of a Lagrange-d'Alembert map and establish a $C^r$ convergence theorem for first-order one-step methods. Building on these results, we propose Generalized Forced Hamiltonian Neural Networks (GFHNNs), a class...

    arxiv.org/abs/2608.19688 · PDF

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