Annealed flow transport monte carlo

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Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics

K Cranmer, G Kanwar, S Racanière… - Nature Reviews …, 2023 - nature.com
Sampling from known probability distributions is a ubiquitous task in computational science,
underlying calculations in domains from linguistics to biology and physics. Generative …
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Ductile-to-brittle transition and yielding in soft amorphous materials: perspectives and open questions

T Divoux, E Agoritsas, S Aime, C Barentin, JL Barrat… - Soft Matter, 2024 - pubs.rsc.org
Soft amorphous materials are viscoelastic solids ubiquitously found around us, from clays
and cementitious pastes to emulsions and physical gels encountered in food or biomedical …
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Improved sampling via learned diffusions

L Richter, J Berner - ar** the replica exchange ladder with normalizing flows
M Invernizzi, A Krämer, C Clementi… - The Journal of Physical …, 2022 - ACS Publications
We combine replica exchange (parallel tempering) with normalizing flows, a class of deep
generative models. These two sampling strategies complement each other, resulting in an …
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