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Inverse problems are ubiquitous because they formalize the integration of data with mathematical models. In many scientific applications the forward model is expensive to evaluate, and adjoint computations are difficult to employ; in this…

Dynamical Systems · Mathematics 2021-11-05 G. A. Pavliotis , A. M. Stuart , U. Vaes

Bayesian calibration is widely used for inverse analysis and uncertainty analysis for complex systems in the presence of both computer models and observation data. In the present work, we focus on large-scale fluid-structure interaction…

Numerical Analysis · Mathematics 2022-01-03 Shunxiang Cao , Daniel Zhengyu Huang

In the square root velocity framework, the computation of shape space distances and the registration of curves requires solution of a non-convex variational problem. In this paper, we present a new PDE-based method for solving this problem…

Numerical Analysis · Mathematics 2021-03-31 Esten Nicolai Wøien , Markus Grasmair

We give a criterion when a planar tree-like curve, i.e. a generic immersed plane curve each double point of which cuts it into two disjoint parts, can be send by a diffeomorphism of the plane onto a curve with no inflection points. We also…

dg-ga · Mathematics 2008-02-03 Boris Shapiro

Membranes holomorphically embedded in flat noncompact space are constructed in terms of the degrees of freedom of an infinite collection of 0-branes. To each holomorphic curve we associate infinite-dimensional matrices which are static…

High Energy Physics - Theory · Physics 2008-11-26 Lorenzo Cornalba , Washington Taylor

The inversion problem for rational B\'ezier curves is addressed by using resultant matrices for polynomials expressed in the Bernstein basis. The aim of the work is not to construct an inversion formula but finding the corresponding value…

Numerical Analysis · Mathematics 2010-07-19 Ana Marco , José-Javier Martinez

Recent advances in machine learning have inspired a surge of research into reconstructing specific quantities of interest from measurements that comply with certain physical laws. These efforts focus on inverse problems that are governed by…

Machine Learning · Statistics 2025-04-23 Honam Wong , Wendao Wu , Fanghui Liu , Yiping Lu

We demonstrate how path integrals often used in problems of theoretical physics can be adapted to provide a machinery for performing Bayesian inference in function spaces. Such inference comes about naturally in the study of inverse…

Data Analysis, Statistics and Probability · Physics 2014-07-23 Joshua C Chang , Van Savage , Tom Chou

A new analytical formulation is prescribed to solve the Helmholtz equation in 2D with arbitrary boundary. A suitable diffeomorphism is used to annul the asymmetries in the boundary by mapping it into an equivalent circle. This results in a…

Quantum Physics · Physics 2013-07-24 Subhasis Panda , Tapomoy Guha Sarkar , S Pratik Khastgir

The Large Deformation Diffeomorphic Metric Mapping (LDDMM) or flow of diffeomorphism is a classical framework in the field of shape spaces and is widely applied in mathematical imaging and computational anatomy. Essentially, it equips a…

Numerical Analysis · Mathematics 2026-02-27 Benedikt Wirth

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior…

Computer Vision and Pattern Recognition · Computer Science 2017-09-18 Zorah Lähner , Matthias Vestner , Amit Boyarski , Or Litany , Ron Slossberg , Tal Remez , Emanuele Rodolà , Alex Bronstein , Michael Bronstein , Ron Kimmel , Daniel Cremers

In this paper, we propose a novel mathematical framework for piecewise diffeomorphic image registration that involves discontinuous sliding motion using a diffeomorphism groupoid and algebroid approach. The traditional Large Deformation…

Group Theory · Mathematics 2026-04-30 Lili Bao , Bin Xiao , Shihui Ying , Stefan Sommer

This paper introduces a novel variational Bayesian method that integrates Tucker decomposition for efficient high-dimensional inverse problem solving. The method reduces computational complexity by transforming variational inference from a…

Machine Learning · Computer Science 2026-03-18 Qing-Mei Yang , Da-Qing Zhang

Farin proposed a method for designing Bezier curves with monotonic curvature and torsion. Such curves are relevant in design due to their aesthetic shape. The method relies on applying a matrix M to the first edge of the control polygon of…

Numerical Analysis · Mathematics 2020-07-21 A. Cantón , L. Fernández-Jambrina , M. J. Vázquez-Gallo

This paper deals with the numerical approximation of the biharmonic inverse source problem in an abstract setting in which the measurement data is finite-dimensional. This unified framework in particular covers the conforming and…

Numerical Analysis · Mathematics 2021-06-15 Devika Shylaja , M. T. Nair

Fitting models to data using Bayesian inference is quite common, but when each point in parameter space gives a curve, fitting the curve to a data set requires new nuisance parameters, which specify the metric embedding the one-dimensional…

Data Analysis, Statistics and Probability · Physics 2018-02-23 Andrew W. Steiner

In this paper, we investigate the data-driven identification of asymmetric interaction kernels in the Motsch-Tadmor model based on observed trajectory data. The model under consideration is governed by a class of semilinear evolution…

Machine Learning · Statistics 2025-05-13 Jinchao Feng , Sui Tang

We discuss hypersurface motions in Riemannian manifolds whose normal velocity is a function of the induced hypersurface volume element and derive a second order partial differential equation for the corresponding time function $\tau(x)$ at…

High Energy Physics - Theory · Physics 2009-10-28 Martin Bordemann , Jens Hoppe

We formulate as an inverse problem the construction of sparse parametric continuous curve models that fit a sequence of contour points. Our prior is incorporated as a regularization term that encourages rotation invariance and sparsity. We…

Image and Video Processing · Electrical Eng. & Systems 2022-06-28 Icíar Lloréns Jover , Thomas Debarre , Shayan Aziznejad , Michael Unser

The geometric approach to diffeomorphic image registration known as "large deformation by diffeomorphic metric mapping" (LDDMM) is based on a left action of diffeomorphisms on images, and a right-invariant metric on a diffeomorphism group,…

Differential Geometry · Mathematics 2014-01-16 Tanya Schmah , Laurent Risser , François-Xavier Vialard