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This paper is devoted to giving definitions of Besov spaces on an arbitrary open set of $\mathbb R^n$ via the spectral theorem for the Schr\"odinger operator with the Dirichlet boundary condition. The crucial point is to introduce some test…

Functional Analysis · Mathematics 2016-03-07 Tsukasa Iwabuchi , Tokio Matsuyama , Koichi Taniguchi

A class of integral transforms, on the planar Gaussian Hilbert space with range in the weighted Bergman space on the bi-disk, is defined as the dual transforms of the 2d fractional Fourier transform associated with the Mehler function for…

Complex Variables · Mathematics 2020-05-19 Abdelhadi Benahmadi , Allal Ghanmi

We analyse the strong connections between spaces of vector-valued Lipschitz functions and spaces of linear continuous operators. We apply these links to study duality, Schur properties and norm attainment in the former class of spaces as…

Functional Analysis · Mathematics 2016-07-20 Luis García-Lirola , Colin Petitjean , Abraham Rueda Zoca

Let $p(\cdot)$ be a measurable function defined on a probability space satisfying $0<p_-:={\rm ess}\inf_{x\in \Omega}p(x)\leq {\rm ess}\sup_{x\in\Omega}p(x)=:p_+<\infty$. We investigate five types of martingale Hardy spaces $H_{p(\cdot)}$…

Probability · Mathematics 2020-01-27 Yong Jiao , Ferenc Weisz , Dejian Zhou , Lian Wu

A Bochner integral formula is derived that represents a function in terms of weights and a parametrized family of functions. Comparison is made to pointwise formulations, norm inequalities relating pointwise and Bochner integrals are…

Functional Analysis · Mathematics 2023-02-28 Paul C. Kainen , A. Vogt

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these…

Materials Science · Physics 2024-05-08 Lorenzo Bastonero , Nicola Marzari

Bayesian nonparametric space partition (BNSP) models provide a variety of strategies for partitioning a $D$-dimensional space into a set of blocks. In this way, the data points lie in the same block would share certain kinds of homogeneity.…

Machine Learning · Statistics 2021-03-02 Xuhui Fan , Bin Li , Ling Luo , Scott A. Sisson

Partial differential equations (PDEs) govern complex systems, yet neural operators often struggle to efficiently capture the long-range, nonlocal interactions inherent in their solution maps. We introduce Spectral Filtering Operator (SFO),…

Machine Learning · Computer Science 2026-01-27 Noam Koren , Rafael Moschopoulos , Kira Radinsky , Elad Hazan

In this paper we define an internal binary operation between functions called in the text \emph{fractal convolution}, that applies a pair of mappings into a fractal function. This is done by means of a suitable Iterated Function System. We…

Classical Analysis and ODEs · Mathematics 2019-07-16 M. A. Navascués , P. Massopust

Partial differential equations often contain unknown functions that are difficult or impossible to measure directly, hampering our ability to derive predictions from the model. Workflows for recovering scalar PDE parameters from data are…

Machine Learning · Computer Science 2026-02-16 Torkel E. Loman , Yurij Salmaniw , Antonio Leon Villares , Jose A. Carrillo , Ruth E. Baker

The subject of this textbook is the analysis of Boolean functions. Roughly speaking, this refers to studying Boolean functions $f : \{0,1\}^n \to \{0,1\}$ via their Fourier expansion and other analytic means. Boolean functions are perhaps…

Discrete Mathematics · Computer Science 2021-05-24 Ryan O'Donnell

In this paper we present a comprehensive treatment of function spaces with logarithmic smoothness (Besov, Sobolev, Triebel-Lizorkin). We establish the following results: Sharp embeddings between the Besov spaces defined by differences and…

Functional Analysis · Mathematics 2018-12-27 Oscar Domínguez , Sergey Tikhonov

Analogy with Bayesian inference is used to formulate constraints within a scheme for functional integration proposed by Cartier and DeWitt-Morette. According to the analogy, functional counterparts of conditional and conjugate probability…

Mathematical Physics · Physics 2014-11-19 J. LaChapelle

We consider an enlarged dimension reduction space in functional inverse regression. Our operator and functional analysis based approach facilitates a compact and rigorous formulation of the functional inverse regression problem. It also…

Statistics Theory · Mathematics 2015-03-13 Ting-Li Chen , Su-Yun Huang , Yanyuan Ma , I-Ping Tu

We propose a functional framework of fractional Sobolev spaces for a class of ultra-parabolic Kolmogorov type operators satisfying the weak H\"ormander condition. We characterize these spaces as real interpolation of natural order intrinic…

Analysis of PDEs · Mathematics 2025-01-13 Antonello Pesce , Sascha Portaro

We consider the tasks of representing, analyzing and manipulating maps between shapes. We model maps as densities over the product manifold of the input shapes; these densities can be treated as scalar functions and therefore are…

Graphics · Computer Science 2019-01-10 Emanuele Rodolà , Zorah Lähner , Alex M. Bronstein , Michael M. Bronstein , Justin Solomon

Deep neural networks have emerged as powerful tools for learning operators defined over infinite-dimensional function spaces. However, existing theories frequently encounter difficulties related to dimensionality and limited…

Machine Learning · Computer Science 2026-05-12 Jianfei Li , Shuo Huang , Han Feng , Ding-Xuan Zhou , Gitta Kutyniok

We explore the Bohr inequality involving the Fourier transforms of complex valued integrable and square integrable functions defined on a second countable compact topological group. We also investigate the connection of the Bohr phenomenon…

Functional Analysis · Mathematics 2020-11-26 Bappaditya Bhowmik , Nilanjan Das

Fractional Differential Equations (FDEs) are essential tools for modelling complex systems in science and engineering. They extend the traditional concepts of differentiation and integration to non-integer orders, enabling a more precise…

Machine Learning · Computer Science 2025-03-27 C. Coelho , M. Fernanda P. Costa , L. L. Ferrás

We propose a method for computing bounds on output functionals of a class of time-dependent PDEs. To this end, we introduce barrier functionals for PDE systems. By defining appropriate unsafe sets and optimization problems, we formulate an…

Optimization and Control · Mathematics 2014-12-11 Mohamadreza Ahmadi , Giorgio Valmorbida , Antonis Papachristodoulou
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