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Frank No'e

3 papers hereh-index 4310 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • physics.chem-ph1
  • stat.ML1
same name
  • Frank No'e — 8 papers, h 14
  • Frank No'e — 6 papers, h 2
  • Frank No'e — 5 papers, h 5
  • Frank No'e — 4 papers, h 3
  • Frank No'e — 2 papers, h 7
  • Frank No'e — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedStatistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

3 citations · 3 across the 1 of their papers we have counts for

collaborators

3 papers

physics.chem-ph2023★ 3 cited

Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

Andreas Krämer, Aleksander P. Durumeric, Nicholas E. Charron +3

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training…

stat.ML2023

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde +5

Molecular dynamics (MD) simulation is a widely used technique to simulate molecular systems, most commonly at the all-atom resolution where equations of motion are integrated with…

cs.LG2023

Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics

Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang +6

Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accur…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.