Organizer: Maria Cameron
When: Friday, 2PM
Where: Kirwan Hall MTH1310
Web Page: https://www.math.umd.edu/~mariakc/rit.html
Description: In recent years, machine learning techniques penetrated a tremendous variety of scientific fields. In particular, they gave rise to data-driven methods for the study of rare event in complex physical systems such as conformational changes in biomolecules, rearrangements of clusters of interacting particles, etc. These methods truly opened new horizons by enabling us to address problems that used to be intractable due to the curse of dimensionality. They are divided into two families: diffusion map-based and neural network-based. In this RIT we will explore methods for the study of rare events based on machine learning.

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  • Organizational meeting

    Speaker: Maria Cameron (UMCP) - https://www.math.umd.edu/~mariakc/

    When: Fri, September 10, 2021 - 2:00pm
    Where: MATH1310
  • Diffusion maps applied to molecular dynamics

    Speaker: Luke Evans (UMCP) - https://www.math.umd.edu/~evansal/

    When: Fri, September 24, 2021 - 2:00pm
    Where: MTH1310
  • Quantifying rare events with the aid of neural networks

    Speaker: Margot Yuan (UMCP) -

    When: Fri, October 8, 2021 - 2:00pm
    Where: Kirwan Hall 1310
  • Analysis of activation functions for neural networks

    Speaker: Manyuan Tao (UMCP) -

    When: Fri, October 15, 2021 - 2:00pm
    Where: Kirwan Hall 1310
  • Self-Assembly of Hydrocarbons

    Speaker: Christopher Moakler (UMCP) -

    When: Fri, October 22, 2021 - 2:00pm
    Where: MATH1310
  • An introduction to density functional theory and quantum many-body problem

    Speaker: Ryan Synk (UMCP, CS) - https://ryansynk.github.io

    When: Fri, November 19, 2021 - 2:00pm
    Where: MATH 1310
  • SpectralNet

    Speaker: Shashank Sule (UMCP) - https://www-math.umd.edu/people/all-directory/item/1564-ssule25.html

    When: Fri, December 3, 2021 - 2:00pm
    Where: MATH 1310