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A multitude of imaging and vision tasks have seen recently a major transformation by deep learning methods and in particular by the application of convolutional neural networks. These methods achieve impressive results, even for…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Simon Arridge , Andreas Hauptmann

In this paper we investigate, through numerical studies, the dynamical evolutions encoded in a linear one-dimensional nonlocal equation arising in peridynamcs. The different propagation regimes ranging from the hyperbolic to the dispersive,…

Pattern Formation and Solitons · Physics 2021-10-19 Giuseppe Maria Coclite , Serena Dipierro , Giuseppe Fanizza , Francesco Maddalena , Marzia Romano , Enrico Valdinoci

We show the well-posedness for a large class of degenerate parabolic equations with an additional singularity and mixed Dirichlet-Neumann boundary conditions on bounded Lipschitz domains. The proof is based on an $L^1$-contraction result.…

Analysis of PDEs · Mathematics 2022-06-27 Victor Hissink Muller , Stefanie Sonner

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian…

Machine Learning · Statistics 2014-02-13 Philipp Hennig , Søren Hauberg

We study the existence and uniqueness of solutions of a nonlinear integro-differential problem which we reformulate introducing the notion of the decreasing rearrangement of the solution. A dimensional reduction of the problem is obtained…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Gonzalo Galiano , Emanuele Schiavi , Julián Velasco

In this paper, we derive a priori estimates for the gradient and second order derivatives of solutions to a class of Hessian type fully nonlinear parabolic equations with the first initial-boundary value problem on Riemannian manifolds.…

Analysis of PDEs · Mathematics 2015-02-04 Ge-Jun Bao , Wei-Song Dong

In image set classification, a considerable advance has been made by modeling the original image sets by second order statistics or linear subspace, which typically lie on the Riemannian manifold. Specifically, they are Symmetric Positive…

Computer Vision and Pattern Recognition · Computer Science 2018-05-31 Rui Wang , Xiao-Jun Wu , Kai-Xuan Chen , Josef Kittler

The space of images can be equipped with a Riemannian metric measuring both the cost of transport of image intensities and the variation of image intensities along motion lines. The resulting metamorphosis model was introduced and analyzed…

Numerical Analysis · Mathematics 2017-05-15 Alexander Effland , Martin Rumpf , Florian Schäfer

We consider non smooth general degenerate/singular parabolic equations in non divergence form with degeneracy and singularity occurring in the interior of the spatial domain, in presence of Dirichlet or Neumann boundary conditions. In…

Analysis of PDEs · Mathematics 2015-09-29 Genni Fragnelli

We establish the convergence theory of multiplicative Diophantine approximation for all non-degenerate, smooth manifolds. We also settle said convergence theory for all affine subspaces satisfying a highly generic and essentially optimal…

Number Theory · Mathematics 2026-02-12 Sam Chow , Rajula Srivastava , Niclas Technau , Han Yu

In this paper, we consider linear ill-posed problems in Hilbert spaces and their regularization via frame decompositions, which are generalizations of the singular-value decomposition. In particular, we prove convergence for a general class…

Numerical Analysis · Mathematics 2022-11-04 Simon Hubmer , Ronny Ramlau , Lukas Weissinger

A class of linear degenerate elliptic equations inspired by nonlinear diffusions of image processing is considered. It is characterized by an interior degeneration of the diffusion coefficient. It is shown that no particularly natural,…

Analysis of PDEs · Mathematics 2018-08-14 Patrick Guidotti

Denoising diffusion models are a novel class of generative algorithms that achieve state-of-the-art performance across a range of domains, including image generation and text-to-image tasks. Building on this success, diffusion models have…

Machine Learning · Computer Science 2024-03-08 Nic Fishman , Leo Klarner , Valentin De Bortoli , Emile Mathieu , Michael Hutchinson

We prove regularity for a class of boundary value problems for first order elliptic systems, with boundary conditions determined by spectral decompositions, under coefficient differentiability conditions weaker than previously known. We…

Differential Geometry · Mathematics 2007-05-23 P. T. Chrusciel , R. Bartnik

We find an explicit form of entropy solutions to a Riemann problem for a degenerate nonlinear parabolic equation with piecewise constant velocity and diffusion coefficients. It is demonstrated that this solution corresponds to the minimum…

Analysis of PDEs · Mathematics 2023-02-01 Evgeny Yu. Panov

We find an explicit form of weak solutions to a Riemann problem for a degenerate semilinear parabolic equation with piecewise constant diffusion coefficient. It is demonstrated that the phase transition lines (free boundaries) correspond to…

Analysis of PDEs · Mathematics 2022-11-01 Evgeny Yu. Panov

This paper is devoted to a fundamental solution of a nonlinear kinetic equation involving a porous medium or fast diffusion operator acting on velocities. Such a nonlinearity has interesting scaling properties, which result in a…

Analysis of PDEs · Mathematics 2026-03-30 Giovanni Brigati , Guillaume Carlier , Jean Dolbeault

In this paper, we investigate the speed of convergence and higher-order asymptotics of solutions to the porous medium equation posed in $\mathbf{R}^N$. Applying a nonlinear change of variables, we rewrite the equation as a diffusion on a…

Analysis of PDEs · Mathematics 2015-05-26 Christian Seis

This article presents a method for solving large-scale linear inverse problems regular- ized with a nonlinear, edge-preserving penalty term such as the total variation or Perona-Malik. In the proposed scheme, the nonlinearity is handled…

Numerical Analysis · Mathematics 2013-09-02 Simon R. Arridge , Marta M. Betcke , Lauri Harhanen

This paper presents a mathematical foundation for physical models in nonlinear optics through the lens of evolutionary equations. It focuses on two key concepts: well-posedness and exponential stability of Maxwell equations, with models…

Analysis of PDEs · Mathematics 2024-12-10 Nils Margenberg , Markus Bause