3 papers
cs.LG2026
Learning Forced Multibody Dynamics on Lie Groups
Martine Dyring Hansen, Marta Ghirardelli, Elena Celledoni +2
We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only position data. By formulating…
cs.LG2026
A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting
Brooks Kinch, Xiaozhe Hu, Yilong Huang +6
For autoregressive modeling of chaotic dynamical systems over long time horizons, the stability of both training and inference is a major challenge in building scientific foundatio…
eess.SY2025
Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics
Martine Dyring Hansen, Elena Celledoni, Benjamin Kwanen Tapley
We introduce a data-driven method for learning the equations of motion of mechanical systems directly from position measurements, without requiring access to velocity data. This is…