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We study comprehensively local properties of functions in complex Sobolev spaces on a bounded open subset of $\mathbb{C}^n$. The main tool is the corresponding functional capacity for the space which is inspired by the global one due to…

Complex Variables · Mathematics 2026-02-17 Ngoc Cuong Nguyen

In this paper, we introduce a method known as polynomial frame approximation for approximating smooth, multivariate functions defined on irregular domains in $d$ dimensions, where $d$ can be arbitrary. This method is simple, and relies only…

Numerical Analysis · Mathematics 2020-05-27 Ben Adcock , Daan Huybrechs

We study the natural function space for infinitely wide two-layer neural networks with ReLU activation (Barron space) and establish different representation formulae. In two cases, we describe the space explicitly up to isomorphism. Using a…

Machine Learning · Statistics 2021-06-07 Weinan E , Stephan Wojtowytsch

We study multivariate integration and approximation for functions belonging to a weighted reproducing kernel Hilbert space based on half-period cosine functions in the worst-case setting. The weights in the norm of the function space depend…

Numerical Analysis · Mathematics 2015-11-23 Christian Irrgeher , Peter Kritzer , Friedrich Pillichshammer

We construct various examples of Sobolev-type functions, defined via upper gradients in metric spaces, that fail to be quasicontinuous or weakly quasicontinuous. This is done with quasi-Banach function lattices $X$ as the function spaces…

Functional Analysis · Mathematics 2025-03-28 Anders Björn , Jana Björn , Lukáš Malý

We introduce Besov spaces with variable smoothness and integrability by using the continuous version of Calder\`on reproducing formula. We show that our space is well-defined, i.e., independent of the choice of basis functions. We…

Functional Analysis · Mathematics 2017-11-27 Douadi Drihem

We study Sobolev type spaces defined in terms of sharp maximal functions on Ahlfors regular subsets of the Euclidean space and the relation between these spaces and traces of classical Sobolev spaces.

Functional Analysis · Mathematics 2011-09-12 Lizaveta Ihnatsyeva , Riikka Korte

This work presents an initial analysis of using bijective mappings to extend the Theory of Functional Connections to non-rectangular two-dimensional domains. Specifically, this manuscript proposes three different mappings techniques: a)…

Numerical Analysis · Mathematics 2020-08-18 Daniele Mortari , David Anas

On a general open set of the euclidean space, we study the relation between the embedding of the homogeneous Sobolev space $\mathcal{D}^{1,p}_0$ into $L^q$ and the summability properties of the distance function. We prove that in the…

Analysis of PDEs · Mathematics 2023-01-31 Lorenzo Brasco , Francesca Prinari , Anna Chiara Zagati

This paper extends the universal approximation property of single-hidden-layer feedforward neural networks beyond compact domains, which is of particular interest for the approximation within weighted $C^k$-spaces and weighted Sobolev…

Machine Learning · Statistics 2025-07-08 Ariel Neufeld , Philipp Schmocker

For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale…

Numerical Analysis · Mathematics 2024-04-17 Miranda Boutilier , Konstantin Brenner , Victorita Dolean

We study integration and $L^2$-approximation of functions of infinitely many variables in the following setting: The underlying function space is the countably infinite tensor product of univariate Hermite spaces and the probability measure…

Numerical Analysis · Mathematics 2026-01-13 Michael Gnewuch , Aicke Hinrichs , Klaus Ritter , Robin Rüßmann

In this paper, the authors propose a new framework under which a theory of generalized Besov-type and Triebel-Lizorkin-type function spaces is developed. Many function spaces appearing in harmonic analysis fall under the scope of this new…

Classical Analysis and ODEs · Mathematics 2014-01-30 Yiyu Liang , Dachun Yang , Wen Yuan , Yoshihiro Sawano , Tino Ullrich

We prove an integral representation result for functionals with growth conditions which give coercivity on the space $SBD^p(\Omega)$, for $\Omega\subset\mathbb{R}^2$. The space $SBD^p$ of functions whose distributional strain is the sum of…

Analysis of PDEs · Mathematics 2018-05-01 Sergio Conti , Matteo Focardi , Flaviana Iurlano

We consider the imbedding inequality || f ||_{L^r(R^d)} <= S_{r,n,d} || f ||_{H^{n}(R^d)}; H^{n}(R^d) is the Sobolev space (or Bessel potential space) of L^2 type and (integer or fractional) order n. We write down upper bounds for the…

Functional Analysis · Mathematics 2007-05-23 C. Morosi , L. Pizzocchero

It is common that a Sobolev space defined on $\mathbb{R}^m$ has a non-compact embedding into an $L^p$-space, but it has subspaces for which this embedding becomes compact. There are three well known cases of such subspaces, the Rellich…

Functional Analysis · Mathematics 2020-03-17 Leszek Skrzypczak , Cyril Tintarev

We prove the density of smooth functions in the modular topology in the Musielak-Orlicz-Sobolev spaces essentially extending the results of Gossez \cite{GJP2} obtained in the Orlicz-Sobolev setting. We impose new systematic regularity…

Functional Analysis · Mathematics 2019-05-14 Youssef Ahmida , Iwona Chlebicka , Piotr Gwiazda , Ahmed Youssfi

A space-filling function is a bijection from the unit line segment to the unit square, cube, or hypercube. The function from the unit line segment is continuous. The inverse function, while well-defined, is not continuous. Space-filling…

Computational Geometry · Computer Science 2015-04-21 Aubrey Jaffer

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 study the complexity of approximate representation and learning of submodular functions over the uniform distribution on the Boolean hypercube $\{0,1\}^n$. Our main result is the following structural theorem: any submodular function is…

Machine Learning · Computer Science 2013-04-03 Vitaly Feldman , Pravesh Kothari , Jan Vondrak