Advances in AI/ML-Driven Sampling for Atomistic Simulations

Presentations

• Walking the surfaces with AI-powered MD simulations

  ORAL · Invited

  March 7, 2024, 12:30 PM – March 7, 2024, 1:06 PM

  Presenters

  • Sapna Sarupria

    University of Minnesota

  Authors

  • Sapna Sarupria

    University of Minnesota

  • Varun Gopal

    University of Minnesota - Twin Cities

  • Salman Bin Kashif

    Clemson University

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• Enhanced Sampling using Birth-Death Algorithm

  ORAL

  March 7, 2024, 1:06 PM – March 7, 2024, 1:18 PM

  Presenters

  • ARCHANA GOPAKUMAR REMANIDEVI

    Max Planck Institute for Polymer Research

  Authors

  • ARCHANA GOPAKUMAR REMANIDEVI

    Max Planck Institute for Polymer Research

  • Benjamin Pampel

    Max Planck Institute for Polymer Research

  • Simon Holbach

    Institut für Mathematik, Johannes Gutenberg-Universität Mainz

  • Lisa Hartung

    Institut für Mathematik, Johannes Gutenberg-Universität Mainz

  • Omar Valsson

    University of North Texas

  • Burkhard Dunweg

    Max Planck Institute for Polymer Research

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• Stochastic Resetting for Enhanced Sampling

  ORAL

  March 7, 2024, 1:18 PM – March 7, 2024, 1:30 PM

  Publication: 1. Ofir Blumer, Shlomi Reuveni, and Barak Hirshberg, The Journal of Physical Chemistry Letters 2022 13 (48), 11230-11236, DOI: 10.1021/acs.jpclett.2c03055
  2. Blumer, Ofir, Shlomi Reuveni, and Barak Hirshberg. "Resetting Metadynamics." arXiv preprint arXiv:2307.06037 (2023).‏

  Presenters

  • Ofir Blumer

    Tel Aviv univercity

  Authors

  • Ofir Blumer

    Tel Aviv univercity

  • Shlomi Reuveni

    Tel Aviv univercity

  • Barak Hirshberg

    Tel Aviv univercity

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• Manifold Learning of Collective Variables for Enhanced Sampling Simulations

  ORAL

  March 7, 2024, 1:30 PM – March 7, 2024, 1:42 PM

  Publication: - 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
  - J. Rydzewski, M. Chen, T. K. Ghosh, and O. Valsson, "Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations", J. Chem. Theory Comput. 18, 7179-7192 (2022) - DOI: 10.1021/acs.jctc.2c00873
  - J. Rydzewski, M. Chen, and O. Valsson, "Manifold Learning in Atomistic Simulations: A Conceptual Review", Mach. Learn.: Sci. Technol. 4, 031001 (2023) - DOI:10.1088/2632-2153/ace81a
  

  Presenters

  • Omar Valsson

    University of North Texas

  Authors

  • Omar Valsson

    University of North Texas

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• Efficient Sampling for Structure Search Using VAE-Organized Latent Spaces and Genetic Algorithms

  ORAL

  March 7, 2024, 1:42 PM – March 7, 2024, 1:54 PM

  Presenters

  • Chaitanya Kolluru

    Argonne National Laboratory

  Authors

  • Chaitanya Kolluru

    Argonne National Laboratory

  • Nina Andrejevic

    Argonne National Laboratory

  • Maria K Chan

    Argonne National Laboratory

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• Complex local environments classification of shape particles through shape-symmetry encoded data augmentation.

  ORAL

  March 7, 2024, 1:54 PM – March 7, 2024, 2:06 PM

  Presenters

  • Alex Lee

    University of Michigan, Ann Arbor, University of Michigan

  Authors

  • Alex Lee

    University of Michigan, Ann Arbor, University of Michigan

  • Sharon C Glotzer

    University of Michigan, University of Michigan, Ann Arbor

  • Sun-Ting Tsai

    University of Michigan, Ann Arbor

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• Learning all-atom molecular reactions using data-driven approaches

  ORAL

  March 7, 2024, 2:06 PM – March 7, 2024, 2:18 PM

  Presenters

  • Julia H Yang

    Harvard University

  Authors

  • Julia H Yang

    Harvard University

  • Whai Shin Amanda Ooi

    Columbia University

  • Zachary A Goodwin

    Harvard University, Imperial College London

  • Yu Xie

    Harvard University

  • Ah-Hyung Alissa Park

    University of California, Los Angeles

  • Boris Kozinsky

    Harvard University

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• Exploring transferability of machine learning interatomic potentials for reactive chemistry

  ORAL

  March 7, 2024, 2:18 PM – March 7, 2024, 2:30 PM

  Publication: Doi.org/10.1039/D3DD00051F

  Presenters

  • Quin H Hu

    University of Minnesota

  Authors

  • Quin H Hu

    University of Minnesota

  • Jason D Goodpaster

    University of Minnesota

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• Active Learning of Diffusion Pathways for Machine-Learned Interatomic Potentials

  ORAL

  March 7, 2024, 2:30 PM – March 7, 2024, 2:42 PM

  Presenters

  • Michael J Waters

    Northwestern University

  Authors

  • Michael J Waters

    Northwestern University

  • James M Rondinelli

    Northwestern University

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• Modeling reaction-diffusion in the liquid-phase heterogeneous catalysis using machine-learned force field.

  ORAL

  March 7, 2024, 2:42 PM – March 7, 2024, 2:54 PM

  Presenters

  • Neeraj Rai

    Mississippi State University

  Authors

  • Neeraj Rai

    Mississippi State University

  • Woodrow Wilson

    Mississippi State Univesity

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• Charge-dependent atomic cluster expansions

  ORAL

  March 7, 2024, 2:54 PM – March 7, 2024, 3:06 PM

  Publication: Goff, James, et al. "Shadow molecular dynamics and atomic cluster expansions for flexible charge models." Journal of Chemical Theory and Computation 19.13 (2023): 4255-4272.

  Presenters

  • James M Goff

    Sandia National Laboratories

  Authors

  • James M Goff

    Sandia National Laboratories

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• Rapidly converging cluster expansions by transfer learning from empirical potentials

  ORAL

  March 7, 2024, 3:06 PM – March 7, 2024, 3:18 PM

  Publication: A. Dana, L. Mu, S.B. Sinnott, I. Dabo , Rapidly converging cluster expansions by transfer learning from empirical potentials. (planned paper)

  Presenters

  • Amirreza Dana

    Pennsylvania State University

  Authors

  • Amirreza Dana

    Pennsylvania State University

  • Ismaila Dabo

    Pennsylvania State University

  • Susan B Sinnott

    Pennsylvania State University

  • Lingxiao Mu

    Pennsylvania State University

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• Accelerated Predictions of Charge Density Evolution in MD simulations Using Machine Learning

  ORAL

  March 7, 2024, 3:18 PM – March 7, 2024, 3:30 PM

  Presenters

  • Aditya Venkatraman

    Sandia National Laboratories

  Authors

  • Aditya Venkatraman

    Sandia National Laboratories

  • Mark A Wilson

    Sandia National Laboratories

  • David Montes de Oca Zapiain

    Sandia National laboratories, Sandia National Laboratories

  View abstract →