Overview Statistic: PDF-Downloads (blue) and Frontdoor-Views (gray)
  • search hit 5 of 331
Back to Result List

Understanding recent deep-learning techniques for identifying collective variables of molecular dynamics

epub ahead of print
  • High-dimensional metastable molecular dynamics (MD) can often be characterised by a few features of the system, that is, collective variables (CVs). Thanks to the rapid advance in the area of machine learning and deep learning, various deep learning-based CV identification techniques have been developed in recent years, allowing accurate modelling and efficient simulation of complex molecular systems. In this paper, we look at two different categories of deep learning-based approaches for finding CVs, either by computing leading eigenfunctions of transfer operator associated to the underlying dynamics, or by learning an autoencoder via minimisation of reconstruction error. We present a concise overview of the mathematics behind these two approaches and conduct a comparative numerical study of these two approaches on illustrative examples.

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics - number of accesses to the document
Metadaten
Author:Wei Zhang, Christof Schütte
Document Type:Article
Parent Title (English):Proceedings in Applied Mathematics and Mechanics
Volume:23
Issue:4
Year of first publication:2023
DOI:https://doi.org/10.1002/pamm.202300189
Accept ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.