Projects funded by the NCN

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Information of the project and the call

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Statistical Learning of Slow Collective Variables from Atomistic Simulations

2021/43/D/ST4/00920

Keywords:

collective variables molecular dynamics enhanced sampling statistical learning

Descriptors:

  • ST4_004:
  • ST3_016:
  • ST3_015:

Panel:

ST4 - Chemistry: physical chemistry/chemical physics, theoretical chemistry, analytical chemistry, inorganic chemistry, organic chemistry, method development

Host institution :

Uniwersytet Mikołaja Kopernika w Toruniu, Wydział Fizyki, Astronomii i Informatyki Stosowanej

woj. kujawsko-pomorskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr Jakub Rydzewski 

Number of co-investigators in the project: 2

Call: SONATA 17 - announced on 2021-09-15

Amount awarded: 769 200 PLN

Project start date (Y-m-d): 2022-07-11

Project end date (Y-m-d): 2026-07-10

Project duration:: 48 months (the same as in the proposal)

Project status: Pending project

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Information in the final report

  • Publication in academic press/journals (4)
  1. Spectral map: Embedding slow kinetics in collective variables
    Authors:
    Jakub Rydzewski
    Academic press:
    Journal of Physical Chemistry Letters (rok: 2023, tom: 14, strony: 5216–5220), Wydawca: ACS
    Status:
    Published
    DOI:
    10.1021/acs.jpclett.3c01101 - link to the publication
  2. Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
    Authors:
    Jakub Rydzewski, Ming Chen, Tushar Ghosh, Omar Valsson
    Academic press:
    Journal of Chemical Theory and Computation (rok: 2022, tom: 18, strony: 7179–7192), Wydawca: ACS
    Status:
    Published
    DOI:
    10.1021/acs.jctc.2c00873 - link to the publication
  3. Manifold Learning in Atomistic Simulations: A Conceptual Review
    Authors:
    Jakub Rydzewski, Ming Chen, Omar Valsson
    Academic press:
    Machine Learning: Science and Technology (rok: 2023, tom: 4, strony: 31001), Wydawca: IOP
    Status:
    Published
    DOI:
    10.1088/2632-2153/ace81a - link to the publication
  4. Selecting High-Dimensional Representations of Physical Systems by Reweighted Diffusion Maps
    Authors:
    Jakub Rydzewski
    Academic press:
    Journal of Physical Chemistry Letters (rok: 2023, tom: 14, strony: 2778–2783), Wydawca: ACS
    Status:
    Published
    DOI:
    10.1021/acs.jpclett.3c00265 - link to the publication

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