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nlin.CD2026
Learning a quantitative criterion for distinguishing chaos from noise
Jaesung Choi, Athokpam Langlen Chanu, Jong-Min Park
Distinguishing chaos from noise using time-series data is fundamentally challenging because both exhibit irregular fluctuations and share many statistical and dynamical characteris…
nlin.CD2026
Extrapolating the emergence of Hamiltonian chaos with random-feature Hamiltonian neural networks
Jaesung Choi
Machine learning of Hamiltonian dynamics has driven growing interest in Hamiltonian neural networks (HNNs), which encode Hamilton's equations of motion into the learning architectu…