ISOKANN learns collective variables via neural Koopman subspaces and derives effective dynamics to compute transition rates, times, and pathways from molecular simulation data.
Exact dynamical coarse-graining without time-scale separation.The Journal of Chemical Physics, 141(4):044109
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Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables
ISOKANN learns collective variables via neural Koopman subspaces and derives effective dynamics to compute transition rates, times, and pathways from molecular simulation data.