Joint Mathematics Meetings MSRI Special Session

Current as of Saturday, January 14, 2023 03:30:04

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• Deadlines
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• Inquiries: meet@ams.org

2023 Joint Mathematics Meetings (JMM 2023)

• John B. Hynes Veterans Memorial Convention Center, Boston Marriott Hotel, and Boston Sheraton Hotel, Boston, MA
• January 4-7, 2023 (Wednesday - Saturday)
• Meeting #1183

Associate Secretary for the AMS Scientific Program:

Steven H. Weintraub, Lehigh University shw2@lehigh.edu

MSRI (SLMath) Special Session on Summer Research in Mathematics (SRiM): Applied and Computational Mathematics

• Wednesday January 4, 2023, 8:00 a.m.-12:00 p.m.
  MSRI (SLMath) Special Session on Summer Research in Mathematics (SRiM): Applied and Computational Mathematics
  Room 208, Hynes Convention Center
  Organizers:
  Yunan Yang, Cornell University yyn0410@gmail.com
  Jingwei Hu, University of Washington
  Yifei Lou, The University of Texas at Dallas
  

  • 8:00 a.m.
    Lipschitz-regularized gradient flows and generative interacting particles
    Hyemin Gu*, University of Massachusetts Amherst
    Markos Katsoulakis, University of Massachusetts Amherst
    (1183-65-20244)
  • 8:30 a.m.
    Revisiting the numerical solution of variational inequalities
    Brendan Keith*, Brown University
    Thomas Surowiec, Philipps-Universität Marburg
    (1183-65-22588)
  • 9:00 a.m.
    Bridging Mean-field Games and Normalizing Flows with Trajectory regularization
    Rongjie Lai*, Rensselaer Polytechnic Institute
    (1183-49-21245)
  • 9:30 a.m.
    Particle-based Stochastic Reaction-Drift-Diffusion Models
    Samuel Isaacson*, Boston University
    (1183-65-20334)
  • 10:00 a.m.
    Fourier representations for fast Gaussian process regression
    Philip Greengard*, Columbia University
    (1183-65-20512)
  • 10:30 a.m.
    Large deviation theory-based adaptive importance sampling for rare events in high dimensions
    Georg Stadler, Courant Institute, New York University
    Shanyin Tong*, Columbia University
    (1183-65-18759)
  • 11:00 a.m.
    Exploiting geometric structure in (matrix-valued) optimization
    Melanie Weber*, Harvard University
    (1183-49-19632)
  • 11:30 a.m.
    Machine learning techniques for high-dimensional optimal control
    Levon Nurbekyan*, Department of Mathematics, UCLA
    (1183-49-18547)