Machine learning and simulation of stochastic dynamics with applications in materials science, September 2023

Lecture Theatre B - Watson Building (R15 on campus map)
Thursday 21 September (12:00) - Friday 22 September 2023 (15:30)

This workshop aims to bring together researchers from applied mathematics and computational chemistry working on machine learning methods and related computational approaches for (or with applications in) materials science.

A particular focus of this workshop will be on methods and mathematical theory that relate to the learning and simulation of (stochastic) dynamics of particle systems including dynamics-preserving coarse-graining techniques, learnable equivariant representations of physical quantities beyond machine-learned interatomic potentials (MLIP), and algorithm design for efficient numerical simulation of relevant dynamics.

The workshop website may be found here.