Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
arXiv:2604.05778v1 Announce Type: cross
Abstract: The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from com…