Geometric Numerical Methods: From Random Fields to Shape Matching
Doktorsavhandling, 2025
optimal transport
Gaussian random fields
Lie–Poisson systems
Stochastic partial differential equations
shape analysis
surface finite element methods
geometric numerical integration
hydrodynamics
Författare
Erik Jansson
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Surface finite element approximation of spherical Whittle-Matérn Gaussian random fields
SIAM Journal of Scientific Computing,;Vol. 44(2022)p. A825-A842
Artikel i vetenskaplig tidskrift
Jansson E., Modin, K. "Sub-Riemannian Landmark Matching and its interpretation as residual neural networks"
CONVERGENCE OF THE VERTICAL GRADIENT FLOW FOR THE GAUSSIAN MONGE PROBLEM
Journal of Computational Dynamics,;Vol. 11(2024)p. 1-9
Artikel i vetenskaplig tidskrift
Jansson E., Krook, J., Modin, K., Öktem, O. "Geometric shape matching for recovering protein conformations from single-particle Cryo-EM data"
Jansson E., Modin, K. "On the numerical signature of blow-up in hydrodynamic equations"
More specifically, this work addresses geometric problems, such as differential equations on curved spaces or mechanical systems, for which it is essential to ensure that the approximate solutions are physically plausible. The applications discussed range from generating random fields on surfaces to reconstructing protein conformations from noisy microscopy data, all of which are inherently geometric problems.
Ämneskategorier (SSIF 2025)
Sannolikhetsteori och statistik
Beräkningsmatematik
Geometri
ISBN
978-91-8103-208-6
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5666
Utgivare
Chalmers
Pascal
Opponent: Professor Stefan Sommer, Department of Computer Science, University of Copenhagen, Denmark