Lecture

Machine-learned force fields for molecular simulation

In course

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Description

This lecture covers the development and application of machine-learned force fields for molecular simulation, focusing on supervised learning methods to predict energy and forces in quantum chemistry. It also discusses the speed-accuracy tradeoff in quantum chemistry simulations and the solution of the electronic Schrödinger equation using machine learning techniques.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_z0m67sb5

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Ontological neighbourhood

Chemistry

Computational chemistry: Topics in computational chemistry

Information engineering

Machine learning: Artificial neural networks

Biological engineering

Biotechnology: Bioinformatics

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