Meta-learning Structure-Preserving Dynamics

ArXi:2508.11205v2 Announce Type: replace Structure-preserving approaches to dynamics discovery have nstrated great potential for modeling physical systems due to their use of strong inductive biases, which enforce key features such as conservation laws and dissipative behavior. However, these models are typically trained on a per-configuration basis, requiring explicit knowledge of system parameters and costly re