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

Published May 13, 2021 | Version 1.0.0

Dataset Open

1. Institute of Physics, Nicolaus Copernicus University, Grudziadzka 5, 87-100 Torun, Poland
2. Max Planck Institute for Polymer Research, Ackermannweg 10, D-55128 Mainz, Germany

MRSE Dataset (version 1.0.0)

Used in the following publications:

J. Rydzewski, and O. Valsson
Multiscale Reweighted Stochastic Embedding: Deep Learning of Collective Variables for Enhanced Sampling
J. 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. Valsson
Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
J. Chem. Theory Comput. 18, 7179 (2022)
doi:10.1021/acs.jctc.2c00873 / arXiv:2207.14554 / plumID:21.023
J. Rydzewski
Selecting High-Dimensional Representations of Physical Systems by Reweighted Diffusion Maps
J. Phys. Chem. Lett. 14, 2778 (2023)
doi:10.1021/acs.jpclett.3c00265 / arXiv:2404.02639
J. Rydzewski, M. Chen, O. Valsson
Manifold Learning in Atomistic Simulations: A Conceptual Review
Mach. Learn.: Sci. Technol. 4, 031001 (2023)
doi:10.1088/2632-2153/ace81a / arXiv:2303.08486

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