Applications-Driven Geometric Functional Data Analysis

Florida State University

Tutorials:

  1. Martin Bauer: Intrinsic and Extrinsic Metrics
  2. Ian Jermyn: Statistics on Riemannian Manifolds
  3. Eric Klassen: Shapes of Curves in Rn
  4. Anuj Srivastava: Introduction to Geometry for Data Analysis
  5. Alain Trouve: A Short Introduction to LDDMM

Scientific Talks:

  1. Nicolas Charon: Shape Analysis through Geometric Distributions
  2. Moo Chung: Hypersperical harmonic (HyperSPHARM) representation
  3. Ian Dryden: Principal nested sub-space analysis on manifolds
  4. Sarang Joshi: Metric Estimation on Landmark Manifolds
  5. Eric Klassen: The Square Root Velocity Framework for Curves in a Homogeneous Space
  6. Sebastian Kurtek: Bayesian Registration of Functions with a Gaussian Process Prior
  7. Alice Le Brigant: Shape analysis of manifold-valued curves using the Square Root Velocity framework
  8. Peter Michor: Overview on analysis and geometries of shape spaces and diffeomorphism groups
  9. Jakob Moeller-Andersen: Varifold-based Curve Matching with Elastic Sobolev Metrics
  10. Tom Needham: Comparing Elastic Metrics on the Space of Plane Curves
  11. Stephen Preston: The Riemannian approach to universal Teichmuller space
  12. Matthew Reimherr: Manifold Data Analysis with Applications to High-Resolution 3D Imaging
  13. Miaomiao Zhang: Frequency Diffeomorphisms For Fast Image Registration