Péter Koltai, Stefan Klus, Gitta Kutyniok, Klaus-Robert Müller, Christof Schütte
Mattes Mollenhauer (FU)
01.01.2019 – 31.12.2021
FU Berlin / ZIB
The transition pathways underlying molecular function are essentially supported by a rather low dimensional manifold. Recent results show how to find such transition manifolds (TM) by embedding techniques. The project aims at finding algorithms for TM learning with quantitative error estimates and for inferring the related effective dynamics by linking ideas from compressed sensing and deep learning to available embedding results.
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