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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Multiscale Reweighted Stochastic Embedding (MRSE): Deep Learning of Collective Variables for Enhanced Sampling

Research datakeyboard_double_arrow_right Dataset 13 May 2021 English Publisher:Zenodo
Authors: Jakub Rydzewski; Omar Valsson;

doi: 10.5281/zenodo.4756093 , 10.5281/zenodo.4756092

Multiscale Reweighted Stochastic Embedding (MRSE): Deep Learning of Collective Variables for Enhanced Sampling

Abstract

MRSE Dataset (version 1.0.0) Used in the following publications: J. Rydzewski, and O. ValssonMultiscale Reweighted Stochastic Embedding: Deep Learning of Collective Variables for Enhanced SamplingJ. Phys. Chem. A 125, 6286 (2021)doi:10.1021/acs.jpca.1c02869 / arXiv:2007.06377 / Zenodo:4756093 / plumID:21.023 J. Rydzewski, M. Chen, T. K. Ghosh, O. ValssonReweighted Manifold Learning of Collective Variables from Enhanced Sampling SimulationsJ. Chem. Theory Comput. 18, 7179 (2022)doi:10.1021/acs.jctc.2c00873 / arXiv:2207.14554 / plumID:21.023 J. RydzewskiSelecting High-Dimensional Representations of Physical Systems by Reweighted Diffusion MapsJ. Phys. Chem. Lett. 14, 2778 (2023)doi:10.1021/acs.jpclett.3c00265 / arXiv:2404.02639 J. Rydzewski, M. Chen, O. ValssonManifold Learning in Atomistic Simulations: A Conceptual ReviewMach. Learn.: Sci. Technol. 4, 031001 (2023)doi:10.1088/2632-2153/ace81a / arXiv:2303.08486

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Keywords

molecular dynamics, enhanced sampling, collective variables, machine learning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
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.
BIP!Impulse provided by BIP!
views
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