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Dataset . 2022
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ZENODO
Dataset . 2022
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ZENODO
Dataset . 2022
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Data sources: Datacite
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Data samples for Flow-matching -- efficient coarse-graining molecular dynamics without forces

Authors: Köhler, Jonas; Chen, Yaoyi; Krämer, Andreas; Clementi, Cecilia; Noé, Frank;

Data samples for Flow-matching -- efficient coarse-graining molecular dynamics without forces

Abstract

We gratefully acknowledge funding from European Commission (Grant No. ERC CoG 772230 "ScaleCell"), the International Max Planck Research School for Biology and Computation (IMPRS–BAC), the BMBF (Berlin Institute for Learning and Data, BIFOLD), the Berlin Mathematics center MATH+ (AA1-6, EF1-2) and the Deutsche Forschungsgemeinschaft DFG (GRK DAEDALUS, SFB1114/A04 and B08). C.C. acknowledges funding from the Deutsche Forschungsgemeinschaft DFG (SFB/TRR 186, Project A12; SFB 1114, Projects B03 and A04; SFB 1078, Project C7; and RTG 2433, Project Q05), the National Science Foundation (CHE-1738990, CHE-1900374, and PHY-2019745), and the Einstein Foundation Berlin (Project 0420815101).

CG samples generated during the training and validation processes in the flow-matching project. Accompanying the preprint "Flow-matching -- efficient coarse-graining molecular dynamics without forces": https://arxiv.org/abs/2203.11167. Detailed descriptions can be found in the preprint as well as the included README.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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