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X-LIC-LOCATION:Europe/Stockholm
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DTSTART:19700308T020000
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DTSTAMP:20230831T095745Z
LOCATION:Schwarzhorn
DTSTART;TZID=Europe/Stockholm:20230626T153000
DTEND;TZID=Europe/Stockholm:20230626T160000
UID:submissions.pasc-conference.org_PASC23_sess167_msa166@linklings.com
SUMMARY:Deep Coarse-Grained Molecular Modeling
DESCRIPTION:Minisymposium\n\nJulija Zavadlav (Technical University of Muni
 ch)\n\nMolecular modeling has become a cornerstone of many disciplines, in
 cluding material science. However, the quality of predictions critically d
 epends on the employed model that defines particle interactions. A class o
 f models with tremendous success in recent years are neural network (NN) p
 otentials due to their flexibility and capacity to learn many-body interac
 tions. In this talk, I will present the current state-of-the-art in deep c
 oarse-grained molecular modeling. I will discuss the ongoing challenge of 
 sufficiently large and broad training datasets and our approaches to allev
 iate this issue, including novel training objectives, combining different 
 data sources, Bayesian uncertainty quantification, and active learning. I 
 will showcase the effectiveness of these approaches for various test case 
 biophysical systems.\n\nDomain: Chemistry and Materials\n\nSession Chair: 
 Julija Zavadlav (Technical University of Munich)
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