arxiv
PublishedJuly 16, 2026 at 4:00 AM
CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts
Publisher summary· verbatim
arXiv:2607.06824v2 Announce Type: replace-cross Abstract: Physics-informed learning promises data-efficient and stable dynamics prediction, yet its strongest geometric guarantees have largely remained confined to closed conservative systems. This excludes robotic systems of interest, where actuation
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Originally published on arxiv ↗