activity
20192022
collaborators

5 papers

cs.GR2022

Sensitive vPSA -- Exploring Sensitivity in Visual Parameter Space Analysis

Bernhard Fröhler, Tim Elberfeld, Torsten Möller +3

The sensitivity of parameters in computational science problems is difficult to assess, especially for algorithms with multiple input parameters and diverse outputs. This work seek…

stat.ME2022

A Nonlinear Hierarchical Model for Longitudinal Data on Manifolds

Martin Hanik, Hans-Christian Hege, Christoph von Tycowicz

Large longitudinal studies provide lots of valuable information, especially in medical applications. A problem which must be taken care of in order to utilize their full potential…

math.ST2020

Bi-invariant Two-Sample Tests in Lie Groups for Shape Analysis

Martin Hanik, Hans-Christian Hege, Christoph von Tycowicz

We propose generalizations of the Hotelling's statistic and the Bhattacharayya distance for data taking values in Lie groups. A key feature of the derived measures is that th…

math.OC2020

Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines

Martin Hanik, Hans-Christian Hege, Anaja Hennemuth +1

Intrinsic and parametric regression models are of high interest for the statistical analysis of manifold-valued data such as images and shapes. The standard linear ansatz has been…

math.OC2019

Geodesic analysis in Kendall's shape space with epidemiological applications

Esfandiar Nava-Yazdani, Hans-Christian Hege, T. J. Sullivan +1

We analytically determine Jacobi fields and parallel transports and compute geodesic regression in Kendall's shape space. Using the derived expressions, we can fully leverage the g…