HITS-SIMPLAIX joint colloquium Frank Noé: Deep Learning for Molecular Physics and Chemistry

By Frank Noé, Freie Universität Berlin, Fachbereich Mathematik und Informatik

AI, and specifically deep ML methods have a profound impact on industry and information technology. But since recently AI methods are also changing the way we do science. In this talk I will present some of our recent efforts to build machine learning methods that attack fundamental problems in physical and chemical sciences: the sampling problem in physical many-body systems, and the solution of the quantum-chemical electronic Schrödinger equation. Key in making progress in these hard problems with ML is to interrogate the physical system about what the learning problem should be, and to encode physical structures, such as symmetries and conservation laws, into the ML model.

Curriculum vitae

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