Joint Mathematics Meetings AMS Special Session

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

• Program
• ·
• Deadlines
• ·
• Timetable
• ·
• 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

AMS Special Session on Topology, Algebra, and Geometry in the Mathematics of Data Science I

• Thursday January 5, 2023, 1:00 p.m.-5:00 p.m.
  AMS Special Session on Topology, Algebra, and Geometry in the Mathematics of Data Science I
  Room 206, Hynes Convention Center
  Organizers:
  Henry Kvinge, Pacific Northwest National Laboratory henry.kvinge@pnnl.gov
  Tim Doster, Pacific Northwest National Laboratory
  Tegan Emerson, Pacific Northwest National Laboratory
  James M. Murphy, Tufts University
  

  • 1:00 p.m.
    Geometric Scattering on Measure Spaces
    Joyce Chew, UCLA
    Matthew Hirn, Michigan State University
    Smita Krishnaswamy, Yale
    Deanna Needell, UCLA
    Michael Perlmutter*, UCLA
    Holly Steach, Yale
    Siddharth Viswanath, UC Irvine
    Hau-tieng Wu, Duke University
    (1183-68-18723)
  • 1:30 p.m.
    Nearly-linear time tools for tensors
    Peter A Brooksbank, Bucknell University
    Martin Kassabov, Cornell University
    James Benjamin Wilson*, Colorado State University
    (1183-15-16292)
  • 2:00 p.m.
    Discrete topological methods for cybersecurity, network science, and machine learning
    Steve Huntsman*, independent
    (1183-55-16804)
  • 2:30 p.m.
    Symmetries of Deep Learning Models and their Internal Representations
    Davis Richard Brown, Pacific Northwest National Laboratory
    Tegan Emerson, Pacific Northwest National Laboratory
    Charles Godfrey*, University of Washington
    Henry Kvinge, Pacific Northwest National Laboratory
    (1183-62-19293)
  • 3:00 p.m.
    Moduli spaces and functional dimension for feedforward ReLU neural networks
    Kathryn Anne Lindsey*, Boston College
    (1183-52-18370)
  • 3:30 p.m.
    Linear Causal Disentanglement
    Anna Seigal*, Harvard University
    Chandler Squires, MIT
    Caroline Uhler, Massachusetts Institute of Technology
    (1183-15-18490)
  • 4:00 p.m.
    Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Analysis
    Shiying Li*, University of North Carolina, Chapel Hill
    (1183-58-17254)
  • 4:30 p.m.
    Properties of model editing
    Davis Richard Brown*, Pacific Northwest National Laboratory
    Charles Godfrey, University of Washington
    Henry Kvinge, Pacific Northwest National Laboratory
    Cody Nizinski, Pacific Northwest National Laboratory
    Jonathan Tu, Pacific Northwest National Laboratory
    (1183-68-20687)
• Friday January 6, 2023, 8:00 a.m.-11:00 a.m.
  AMS Special Session on Topology, Algebra, and Geometry in the Mathematics of Data Science II
  Republic B, Sheraton Boston Hotel
  Organizers:
  Henry Kvinge, Pacific Northwest National Laboratory henry.kvinge@pnnl.gov
  Tim Doster, Pacific Northwest National Laboratory
  Tegan Emerson, Pacific Northwest National Laboratory
  James M. Murphy, Tufts University
  

  • 8:00 a.m.
    Covering point-sets with parallel hyperplanes and sparse signal recovery
    Lenny Fukshansky*, Claremont McKenna College
    Alexander Hsu, University of Washington
    (1183-52-15726)
  • 8:30 a.m.
    nervePool: A Simplicial Pooling Layer
    Matthew Hirn, Michigan State University
    Sarah McGuire*, Michigan State University
    Elizabeth Munch, Michigan State University
    (1183-57-18892)
  • 9:00 a.m.
    Supervised learning of sheared distributions using linearized optimal transport.
    Varun Khurana*, University of California, San Diego
    (1183-49-18988)
  • 9:30 a.m.
    Understanding Deep Learning using Topological Dynamical Systems, Index Theory, and Homology
    Stephen Baek, Univirsity of Virginia, School of Data Science
    Bill Basener*, University of Virginia, School of Data Science
    (1183-57-15271)
  • 10:00 a.m.
    Implicit Bias of Linear Equivariant Networks
    Andrew Dienes, MIT
    Kristian Georgiev, MIT
    Bobak Kiani, MIT
    Hannah Lawrence*, MIT
    (1183-68-21502)
  • 10:30 a.m.
    Multivariate ranks via entropy regularized optimal transport: sample efficiency, goodness-of-fit measures, and applications
    Shuchin Aeron*, Tufts University
    (1183-62-20879)
• Friday January 6, 2023, 1:00 p.m.-6:00 p.m.
  AMS Special Session on Topology, Algebra, and Geometry in the Mathematics of Data Science III
  Republic B, Sheraton Boston Hotel
  Organizers:
  Henry Kvinge, Pacific Northwest National Laboratory henry.kvinge@pnnl.gov
  Tim Doster, Pacific Northwest National Laboratory
  Tegan Emerson, Pacific Northwest National Laboratory
  James M. Murphy, Tufts University
  

  • 1:00 p.m.
    Geometric Approaches to Anomaly Detection and Multiple Data Modalities with Circadian Time Series in Mice
    Manuchehr Aminian*, Cal Poly Pomona
    Helene Andrews-Polymenis, Texas A&M University
    Aravindh Nagarajan, Texas A&M University
    Kristin Scoggin, Texas A&M University
    (1183-62-22454)
  • 1:30 p.m.
    Manifold Reconstruction and Denoising from Scattered Data in High Dimension
    Shira Faigenbaum-Golovin*, Phillip Griffiths Assistant Research Professor, Department of Mathematics, Duke University
    David Levin, Professor, School of Mathematical Sciences, Tel Aviv University, Israel
    (1183-41-21214)
  • 2:00 p.m.
    The Effect of Parametrization on Nonconvex Optimization Landscapes
    Joe Kileel*, University of Texas at Austin
    (1183-65-21423)
  • 2:30 p.m.
    Geometric Data Science: old challenges and new solutions
    Vitaliy A Kurlin*, University of Liverpool (UK)
    (1183-52-21453)
  • 3:00 p.m.
    An Application of the Delaunay-Rips Complex to Sleep-Wake Classification Using Heart Rate Data
    Amish Mishra*, Florida Atlantic University
    (1183-55-22284)
  • 3:30 p.m.
    Statistically and computationally efficient signal recovery with non-expansive generative network priors
    Jorio Cocola*, Harvard University
    (1183-68-21621)
  • 4:00 p.m.
    Persistent Homology of Coarse Grained State Space Networks for Dynamic State Analysis of Time Series
    Firas Khasawneh, Michigan State University
    Elizabeth Munch, Michigan State University
    Audun Myers*, Pacific Northwest National Laboratory
    (1183-55-21693)
  • 4:30 p.m.
    Learning Convex Regularizers
    Eliza O'Reilly*, Caltech
    (1183-52-21854)
  • 5:00 p.m.
    Learning to Solve Hard Minimal Problems
    Timothy Duff*, University of Washington
    (1183-68-21907)
  • 5:30 p.m.
    Wasserstein Labeled Graph Metrics and Stabilities for Clustering
    Michael G Rawson*, PNNL
    (1183-55-22671)