47 !
Sun, 8/8/2021,
3:30 PM -
5:20 PM
Virtual
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
