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220446 ! Sun, 8/8/2021, 3:30 PM - 5:20 PM
Geometric and Topological Information in Data Analysis — Topic Contributed Papers
IMS, Section on Statistical Learning and Data Science, Section on Statistics in Imaging
Organizer(s): Hengrui Luo, Lawrence Berkeley National Laboratory
Chair(s): Chul Moon, Southern Methodist University
3:35 PM Characterizing Heterogenous Information in Persistent Homology with Applications to Molecular Structure Modeling
Zixuan Cang, University of California, Irvine; Guowei Wei, Michigan State Univesity
3:55 PM Gromov-Wasserstein Learning in a Riemannian Framework
Samir Chowdhury, Stanford University
4:15 PM Density Estimation and Modeling on Symmetric Spaces
Didong Li, Princeton University; Yulong Lu, University of Massachusetts Amherst; Emmanuel Chevallier, Aix Marseille University; David Dunson, Duke University
4:35 PM Convergence of Persistence Diagram in the Subcritical Regime
Takashi Owada, Purdue University, Department of Statistics
4:55 PM Combining Geometric and Topological Information for Boundary Estimation
Justin Strait, University of Georgia; Hengrui Luo, Lawrence Berkeley National Laboratory
Discussant: Hengrui Luo, Lawrence Berkeley National Laboratory
5:15 PM Floor Discussion