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We investigate smooth approximations of functions, with prescribed gradient behavior on a distinguished stratified subset of the domain. As an application, we outline how our results yield important consequences for a recently introduced…

Classical Analysis and ODEs · Mathematics 2015-07-21 D. Drusvyatskiy , M. Larsson

Approximating a function with a finite series, e.g., involving polynomials or trigonometric functions, is a critical tool in computing and data analysis. The construction of such approximations via now-standard approaches like least squares…

Optimization and Control · Mathematics 2021-08-30 Dihan Dai , Yekaterina Epshteyn , Akil Narayan

An abstract theory of ultradifferentiable sheafs is developed. Moreover, various applications to the theory of linear partial differential equations, differential geometry and, in particular, CR geometry are discussed.

Analysis of PDEs · Mathematics 2026-03-13 Stefan Fürdös

We find explicit subdivision rules for all special cubulated groups. A subdivision rule for a group produces a sequence of tilings on a sphere which encode all quasi-isometric information for a group. We show how these tilings detect…

Geometric Topology · Mathematics 2013-10-29 Brian Rushton

We present and analyze a semi-discrete finite element scheme for a system consisting of a geometric evolution equation for a curve and a parabolic equation on the evolving curve. More precisely, curve shortening flow with a forcing term…

Numerical Analysis · Mathematics 2015-10-22 Paola Pozzi , Bjorn Stinner

Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenarios where training samples are readily available, which is not…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Ayush Tewari , Tianwei Yin , George Cazenavette , Semon Rezchikov , Joshua B. Tenenbaum , Frédo Durand , William T. Freeman , Vincent Sitzmann

Most approximation methods in high dimensions exploit smoothness of the function being approximated. These methods provide poor convergence results for non-smooth functions with kinks. For example, such kinks can arise in the uncertainty…

Numerical Analysis · Mathematics 2019-02-19 Barbara Fuchs , Jochen Garcke

Subdifferentials (in the sense of convex analysis) of matrix-valued functions defined on $\mathbb{R}^d$ that are convex with respect to the L\"{o}wner partial order can have a complicated structure and might be very difficult to compute…

Optimization and Control · Mathematics 2024-07-22 M. V. Dolgopolik

Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm…

Computational Physics · Physics 2023-09-27 Vidushi Sharma , Lee A. Collins , Alexander J. White

We consider subdiffusion of a particle in a one-dimensional system with a thin partially permeable wall. Passing through the wall, the particle can be absorbed with a certain probability. We call such a wall partially permeable partially…

Statistical Mechanics · Physics 2021-02-17 Tadeusz Kosztołowicz

Steepest descent is central in variational mathematics. We present a new transparent existence proof for curves of near-maximal slope --- an influential notion of steepest descent in a nonsmooth setting. We moreover show that for…

Optimization and Control · Mathematics 2013-05-08 D. Drusvyatskiy , A. D. Ioffe , A. S. Lewis

In a previous paper, an implementable algorithm was introduced to compute discrete solutions of sweeping processes (i.e. specific first order differential inclusions). The convergence of this numerical scheme was proved thanks to…

Numerical Analysis · Mathematics 2014-03-31 Frederic Bernicot , Juliette Venel

In this note we construct solutions to rough differential equations ${\rm d} Y = f(Y) \,{\rm d} X$ with a driver $X \in C^\alpha([0,T];\mathbb{R}^d)$, $\frac13 < \alpha \le \frac12$, using a splitting-up scheme. We show convergence of our…

Classical Analysis and ODEs · Mathematics 2024-12-03 Peter H. C. Pang

The increased availability of massive data sets provides a unique opportunity to discover subtle patterns in their distributions, but also imposes overwhelming computational challenges. To fully utilize the information contained in big…

Statistics Theory · Mathematics 2018-04-12 Stanislav Volgushev , Shih-Kang Chao , Guang Cheng

Pyramid transforms are constructive methods for analyzing sequences in a multiscale fashion. Traditionally, these transforms rely on stationary upsampling and downsampling operations. In this paper, we propose employing nonstationary…

Numerical Analysis · Mathematics 2025-07-15 Hadar Landau , Wael Mattar , Nir Sharon

This book deals with functions allowing to express the dissimilarity (discrepancy) between two data fields or ''divergence functions'' with the aim of applications to linear inverse problems. Most of the divergences found in the litterature…

Optimization and Control · Mathematics 2020-03-04 Henri Lantéri

We introduce the space of grid functions, a space of generalized functions of nonstandard analysis that provides a coherent generalization both of the space of distributions and of the space of Young measures. We will show that in the space…

Functional Analysis · Mathematics 2019-07-15 Emanuele Bottazzi

A Frontal-Delaunay refinement algorithm for mesh generation in piecewise smooth domains is described. Built using a restricted Delaunay framework, this new algorithm combines a number of novel features, including: (i) an unweighted,…

Computational Geometry · Computer Science 2016-07-27 Darren Engwirda

Convexity splitting like schemes with improved accuracy are proposed for a phase field model for surface diffusion. The schemes are developed to enable large scale simulations in three spatial dimensions describing experimentally observed…

Numerical Analysis · Mathematics 2019-11-04 Rainer Backofen , Steven M. Wise , Marco Salvalaglio , Axel Voigt

In two earlier papers, we designed a distributed deterministic asynchronous algorithm for minimizing the sum of subdifferentiable and proximable functions and a regularizing quadratic on time-varying graphs based on Dykstra's algorithm, or…

Optimization and Control · Mathematics 2018-08-23 C. H. Jeffrey Pang
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