Analyzing dynamical brain functional connectivity as trajectories on space of covariance matrices

M Dai, Z Zhang, A Srivastava - IEEE transactions on medical …, 2019 - ieeexplore.ieee.org
Human brain functional connectivity (FC) is often measured as the similarity of functional
MRI responses across brain regions when a brain is either resting or performing a task. This …

Statistical shape analysis of brain arterial networks (BAN)

X Guo, A Basu Bal, T Needham… - The Annals of Applied …, 2022 - projecteuclid.org
Statistical shape analysis of brain arterial networks (BAN) Page 1 The Annals of Applied
Statistics 2022, Vol. 16, No. 2, 1130–1150 https://doi.org/10.1214/21-AOAS1536 © Institute of …

An information geometry approach to robustness analysis for the uncertainty quantification of computer codes

C Gauchy, J Stenger, R Sueur, B Iooss - Technometrics, 2022 - Taylor & Francis
Robustness analysis is an emerging field in the uncertainty quantification domain. It involves
analyzing the response of a computer model—which has inputs whose exact values are …

Intrinsic riemannian metrics on spaces of curves: Theory and computation

M Bauer, N Charon, E Klassen, A Le Brigant - Handbook of Mathematical …, 2021 - Springer
This chapter reviews some past and recent developments in shape comparison and
analysis of curves based on the computation of intrinsic Riemannian metrics on the space of …

Computing distances and geodesics between manifold-valued curves in the SRV framework

AL Brigant - arxiv preprint arxiv:1601.02358, 2016 - arxiv.org
This paper focuses on the study of open curves in a Riemannian manifold M, and proposes
a reparametrization invariant metric on the space of such paths. We use the square root …

Automated characterization and monitoring of material shape using Riemannian geometry

A Smith, S Schilling, P Daoutidis - Computers & Chemical Engineering, 2024 - Elsevier
Shape affects both the physical and chemical properties of a material. Characterizing the
roughness, convexity, and general geometry of a material can yield information on its …

Using a Riemannian elastic metric for statistical analysis of tumor cell shape heterogeneity

W Li, A Prasad, N Miolane, K Dao Duc - International Conference on …, 2023 - Springer
We examine how a specific instance of the elastic metric, the Square Root Velocity (SRV)
metric, can be used to study and compare cellular morphologies from the contours they form …

Learning from landmarks, curves, surfaces, and shapes in Geomstats

LF Pereira, AL Brigant, A Myers, E Hartman… - arxiv preprint arxiv …, 2024 - arxiv.org
We introduce the shape module of the Python package Geomstats to analyze shapes of
objects represented as landmarks, curves and surfaces across fields of natural sciences and …

Representation and characterization of nonstationary processes by dilation operators and induced shape space manifolds

M Dugast, G Bouleux, E Marcon - Entropy, 2018 - mdpi.com
We proposed in this work the introduction of a new vision of stochastic processes through
geometry induced by dilation. The dilation matrices of a given process are obtained by a …

Functional inference on rotational curves under sample‐specific group actions and identification of human gait

FJE Telschow, MR Pierrynowski… - … Journal of Statistics, 2021 - Wiley Online Library
Inspired by the problem of gait reproducibility (reidentifying individuals across doctor's visits)
we develop two‐sample permutation tests under a sample‐specific group action on Lie …