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Data-driven reduced order models (ROMs) are combined with the Lippmann-Schwinger integral equation to produce a direct nonlinear inversion method. The ROM is viewed as a Galerkin projection and is sparse due to Lanczos orthogonalization.…

Numerical Analysis · Mathematics 2021-08-11 Vladimir Druskin , Shari Moskow , Mikhail Zaslavsky

We study kernel functions, and associated reproducing kernel Hilbert spaces $\mathscr{H}$ over infinite, discrete and countable sets $V$. Numerical analysis builds discrete models (e.g., finite element) for the purpose of finding…

Functional Analysis · Mathematics 2015-08-17 Palle Jorgensen , Feng Tian

Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such models under adaptive data collection remain limited. Existing analyses largely focus on…

Machine Learning · Statistics 2026-05-14 Rafael Oliveira

We study a new approach to the problem of transparent boundary conditions for the Helmholtz equation in unbounded domains. Our approach is based on the minimization of an integral functional arising from a volume integral formulation of the…

Analysis of PDEs · Mathematics 2015-06-12 Giulio Ciraolo , Francesco Gargano , Vincenzo Sciacca

Let X and Y be planar Jordan domains of the same finite connectivity, Y being inner chordarc regular (such are Lipschitz domains). Every homeomorphism h:X->Y in the Sobolev space $W^{1,2}$ extends to a continuous map between closed domains.…

Complex Variables · Mathematics 2013-02-12 Tadeusz Iwaniec , Leonid V. Kovalev , Jani Onninen

We present the first optimal rates for infinite-dimensional vector-valued ridge regression on a continuous scale of norms that interpolate between $L_2$ and the hypothesis space, which we consider as a vector-valued reproducing kernel…

Machine Learning · Statistics 2024-08-07 Zhu Li , Dimitri Meunier , Mattes Mollenhauer , Arthur Gretton

We use heat kernels or eigenfunctions of the Laplacian to construct local coordinates on large classes of Euclidean domains and Riemannian manifolds (not necessarily smooth, e.g. with $\mathcal{C}^\alpha$ metric). These coordinates are…

Analysis of PDEs · Mathematics 2008-10-09 Peter W. Jones , Mauro Maggioni , Raanan Schul

It is well known that derivatives of solutions to elliptic boundary value problems may become unbounded near the corner of a domain with a conical singularity, even if the data are smooth. When the corner domain is approximated by more…

Analysis of PDEs · Mathematics 2025-10-08 Martin Costabel , Monique Dauge

We investigate the regularity of linear stochastic parabolic equations with zero Dirichlet boundary condition on bounded Lipschitz domains $O \subset R^d$ with both theoretical and numerical purpose. We use N.V. Krylov's framework of…

Probability · Mathematics 2016-03-31 Petru A. Cioica , Kyeong-Hun Kim , Kijung Lee , Felix Lindner

In this work we develop a new numerical approach for recovering a spatially dependent source component in a standard parabolic equation from partial interior measurements. We establish novel conditional Lipschitz stability and H\"{o}lder…

Numerical Analysis · Mathematics 2025-08-22 Tianhao Hu , Xinchi Huang , Bangti Jin , Qimeng Quan , Zhi Zhou

Inverse scattering has a broad applicability in quantum mechanics, remote sensing, geophysical, and medical imaging. This paper presents a robust direct reduced order model (ROM) method for solving inverse scattering problems based on an…

Numerical Analysis · Mathematics 2023-11-29 Justin Baker , Elena Cherkaev , Vladimir Druskin , Shari Moskow , Mikhail Zaslavsky

This paper is concerned with the ubiquitous inverse problem of recovering an unknown function u from finitely many measurements possibly affected by noise. In recent years, inversion methods based on linear approximation spaces were…

Numerical Analysis · Mathematics 2022-10-06 Albert Cohen , Matthieu Dolbeault , Olga Mula , Agustin Somacal

A new representation is proposed for functions in a Sobolev space with dominating mixed smoothness on an $N$-dimensional hyperrectangle. In particular, it is shown that these functions can be expressed in terms of their highest-order mixed…

Numerical Analysis · Mathematics 2024-04-30 Declan S. Jagt , Matthew M. Peet

In the present paper we consider minimization based formulations of inverse problems $(x,\Phi)\in\mbox{argmin}\{\mathcal{J}(x,\Phi;y)\colon(x,\Phi)\in M_{ad}(y) \}$ for the specific but highly relevant case that the admissible set…

Optimization and Control · Mathematics 2018-07-31 Philipp Hungerländer , Barbara Kaltenbacher , Franz Rendl

We construct a differentiable locally Lipschitz function $f$ in $\mathbb{R}^{N}$ with the property that for every convex body $K\subset \mathbb{R}^N$ there exists $\bar x \in \mathbb{R}^N$ such that $K$ coincides with the set $\partial_L…

Classical Analysis and ODEs · Mathematics 2024-09-13 Aris Daniilidis , Robert Deville , Sebastian Tapia-Garcia

Kernel-based methods in Numerical Analysis have the advantage of yielding optimal recovery processes in the "native" Hilbert space $\calh$ in which they are reproducing. Continuous kernels on compact domains have an expansion into…

Numerical Analysis · Mathematics 2018-10-09 Gabriele Santin , Robert Schaback

Recently Gigli developed a Sobolev calculus on non-smooth spaces using module theory. In this paper it is shown that his theory fits nicely into the theory of differentiability spaces initiated by Cheeger, Keith and others. A relaxation…

Metric Geometry · Mathematics 2015-12-03 Martin Kell

A basilar property and a useful tool in the theory of Sobolev spaces is the density of smooth compactly supported functions in the space $W^{k,p}(\R^n)$ (i.e. the functions with weak derivatives of orders $0$ to $k$ in $L^p$). On Riemannian…

Analysis of PDEs · Mathematics 2023-02-15 Giona Veronelli

In this article we present a modification of classical Radial Basis Function (RBF) interpolation techniques aimed at reducing oscillations near discontinuities in one and two dimensions. Our approach introduces an adaptive mechanism by…

Numerical Analysis · Mathematics 2026-03-25 José Kuruc , David Levin , Pep Mulet , Juan Ruiz-Álvarez , Dionisio F. Yáñez

We propose new optimal estimators for the Lipschitz frontier of a set of points. They are defined as kernel estimators being sufficiently regular, covering all the points and whose associated support is of smallest surface. The estimators…

Methodology · Statistics 2011-03-31 Stéphane Girard , Anatoli Iouditski , Alexander Nazin
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