Výsledky vyhledávání - "Zofia Trstanova"

Local and Global Perspectives on Diffusion Maps in the Analysis of Molecular Systems

Autor: Tony Lelièvre, Ben Leimkuhler, Zofia Trstanova

Publikováno v: Trstanova, Z, Leimkuhler, B & Lelievre, T 2020, ' Local and Global Perspectives on Diffusion Maps in the Analysis of Molecular Systems ', Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 476, no. 2233, 20190036 . https://doi.org/10.1098/rspa.2019.0036
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020, 476 (2233), ⟨10.1098/rspa.2019.0036⟩
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Royal Society, The, 2020, 476 (2233), ⟨10.1098/rspa.2019.0036⟩
Proceedings. Mathematical, Physical, and Engineering Sciences

Diffusion maps approximate the generator of Langevin dynamics from simulation data. They afford a means of identifying the slowly evolving principal modes of high-dimensional molecular systems. When combined with a biasing mechanism, diffusion maps c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10e63b85056f35679c3830efa1e40612
https://www.pure.ed.ac.uk/ws/files/128886956/Local_and_Global_Perspectives_on_Diffusion_Maps_in_the_Analysis_of_Molecular_Systems.pdf

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Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems

Autor: Zineb Belkacemi, Christine Peter, Hervé Minoux, Gabriel Stoltz, Ana J. Silveira, Paraskevi Gkeka, Rafal P. Wiewiora, Alexandre Tkatchenko, Amir Barati Farimani, Tony Lelièvre, John D. Chodera, Fabio Pietrucci, Zofia Trstanova, Michele Ceriotti, Jean-Bernard Maillet, Andrew L. Ferguson, Aaron R. Dinner

Publikováno v: Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation, 2020, ⟨10.1021/acs.jctc.0c00355⟩
J Chem Theory Comput
Journal of Chemical Theory and Computation, American Chemical Society, 2020, ⟨10.1021/acs.jctc.0c00355⟩

This work came out of a CECAM discussion meeting.; International audience; Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38a6573ffae65a8f0ef5142e25a0cb2e

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Transferability of Operational Status Classification Models Among Different Wind Turbine Typesq

Autor: Sergio A. Jimenez, T. Van Delft, Michael Wilkinson, Charles Matthews, Anton Martinsson, Benedict Leimkuhler, Zofia Trstanova

A detailed understanding of wind turbine performance status classification can improve operations and maintenance in the wind energy industry. Due to different engineering properties of wind turbines, the standard supervised learning models used for

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dbcab84955082954c5800ec2000bea2

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Error Analysis of Modified Langevin Dynamics

Autor: Stephane Redon, Gabriel Stoltz, Zofia Trstanova

Publikováno v: Journal of Statistical Physics
Journal of Statistical Physics, Springer Verlag, 2016, 164 (4), pp.735-771. ⟨10.1007/s10955-016-1544-6⟩
Journal of Statistical Physics, 2016, 164 (4), pp.735-771. ⟨10.1007/s10955-016-1544-6⟩

International audience; We consider Langevin dynamics associated with a modified kinetic energy vanishing for small momenta. This allows us to freeze slow particles, and hence avoid the re-computation of inter-particle forces, which leads to computat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7036167cd683fb88f07741764f5b4e3d
https://doi.org/10.1007/s10955-016-1544-6

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Diffusion maps tailored to arbitrary non-degenerate Ito processes

Autor: Péter Koltai, Zofia Trstanova, Andreas Bittracher, Stefan Klus, Ralf Banisch

We present two generalizations of the popular diffusion maps algorithm. The first generalization replaces the drift term in diffusion maps, which is the gradient of the sampling density, with the gradient of an arbitrary density of interest which is

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Langevin dynamics with general kinetic energies

Autor: Gabriel Stoltz, Zofia Trstanova

Publikováno v: Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal
Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 2018, 16 (2), pp.777-806. ⟨10.1137/16M110575X⟩
Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 2018, 16 (2), pp.777-806. ⟨10.1137/16M110575X⟩

International audience We study Langevin dynamics with a kinetic energy different from the standard, quadratic one in order to accelerate the sampling of Boltzmann-Gibbs distributions. In particular, this kinetic energy can be nonglobally Lipschitz,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3df4f41271205141f691523078bc495
http://arxiv.org/abs/1609.02891

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Estimating the speed-up of Adaptively Restrained Langevin Dynamics

Autor: Zofia Trstanova, Stephane Redon

We consider Adaptively Restrained Langevin dynamics, in which the kinetic energy function vanishes for small velocities. Properly parameterized, this dynamics makes it possible to reduce the computational complexity of updating inter-particle forces,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fa1bc52a20673b733c207f8a1bd5dfb
http://arxiv.org/abs/1607.01489

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