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Previously unknown estimates of uniform continuity of projection operators in Banach space have been obtained. They can be used in the investigations of approximation methods, in particular, the method of quasisolutions, methods of…

funct-an · Mathematics 2008-02-03 Ya. I. Alber , A. I. Notik

Deep Operator Networks (DeepONets) provide a branch-trunk neural architecture for approximating nonlinear operators acting between function spaces. In the classical operator approximation framework, the input is a function $u\in C(K_1)$…

Machine Learning · Computer Science 2026-03-13 Vugar Ismailov

Operator learning problems arise in many key areas of scientific computing where Partial Differential Equations (PDEs) are used to model physical systems. In such scenarios, the operators map between Banach or Hilbert spaces. In this work,…

Machine Learning · Computer Science 2024-10-31 Ben Adcock , Nick Dexter , Sebastian Moraga

We prove several abstract results giving general conditions under which subspaces of linear or multilinear operators on Banach spaces or Banach lattices are closed. Each of these abstract results is followed by concrete applications,…

Functional Analysis · Mathematics 2026-05-25 Geraldo Botelho , Ariel Monção

The concept of uniform convexity of a Banach space was generalized to linear operators between Banach spaces and studied by Beauzamy [1976]. Under this generalization, a Banach space X is uniformly convex if and only if its identity map I_X…

Functional Analysis · Mathematics 2007-05-23 J Wenzel

Neural operator architectures employ neural networks to approximate operators mapping between Banach spaces of functions; they may be used to accelerate model evaluations via emulation, or to discover models from data. Consequently, the…

Machine Learning · Computer Science 2025-03-11 Samuel Lanthaler , Andrew M. Stuart

We study a notion analogous to the $p$-Approximation Property ($p$-AP) for Banach spaces, within the noncommutative context of operator spaces. Referred to as the $p$-Operator Approximation Property ($p$-OAP), this concept is linked to the…

Functional Analysis · Mathematics 2025-06-09 Javier Alejandro Chávez-Domínguez , Verónica Dimant , Daniel Galicer

In this paper, we obtained some global approximation results for general Gamma type operators.

General Mathematics · Mathematics 2015-08-28 Alok Kumar

Real linear operators between two complex Banach spaces unify naturally two important classes of linear operators and antilinear operators. We give a survey of basic geometric, spectral and duality properties of real linear operators. The…

Functional Analysis · Mathematics 2025-08-07 Damian Kołaczek , Vladimir Müller

This paper is concerned with general $n\times n$ upper triangular operator matrices with given diagonal entries. We characterize perturbations of the left (right) essential spectrum, the essential spectrum, as well as the left (right) the…

Functional Analysis · Mathematics 2021-08-30 Nikola Sarajlija

Neural operators are neural network-based surrogate models for approximating solution operators of parametric partial differential equations, enabling efficient many-query computations in science and engineering. Many applications,…

Numerical Analysis · Mathematics 2026-02-03 Mingyu Han , Daniel Zhengyu Huang , Yuhan Wang , Yanshu Zhang , Jiayi Zhou

Coupled oscillators are being increasingly used as the basis of machine learning (ML) architectures, for instance in sequence modeling, graph representation learning and in physical neural networks that are used in analog ML devices. We…

Neural and Evolutionary Computing · Computer Science 2023-05-16 Samuel Lanthaler , T. Konstantin Rusch , Siddhartha Mishra

Generalizing classical results of the theory of absolutely summing operators, in this paper we characterize the duals of a quite large class of Banach operator ideals defined or characterized by the transformation of vector-valued…

Functional Analysis · Mathematics 2020-10-06 Geraldo Botelho , Jamilson R. Campos

Neural networks (NNs) are known for their high predictive accuracy in complex learning problems. Beside practical advantages, NNs also indicate favourable theoretical properties such as universal approximation (UA) theorems. Binarized…

Machine Learning · Computer Science 2021-02-05 Mikail Yayla , Mario Günzel , Burim Ramosaj , Jian-Jia Chen

Arbitrary operator A on a Banach space X which is the generator of C_0-group with certain growth condition at infinity is considered. The relationship between its exponential type entire vectors and its spectral subspaces is found. Inverse…

Functional Analysis · Mathematics 2011-03-11 S. Torba

For Banach spaces $X,Y,$ we consider a distance problem in the space of bounded linear operators $\mathcal{L}(X,Y).$ Motivated by a recent paper \cite{RAO21}, we obtain sufficient conditions so that for a compact operator…

Functional Analysis · Mathematics 2022-03-22 Arpita Mal

As an emerging paradigm in scientific machine learning, neural operators aim to learn operators, via neural networks, that map between infinite-dimensional function spaces. Several neural operators have been recently developed. However, all…

Machine Learning · Computer Science 2022-02-15 Pengzhan Jin , Shuai Meng , Lu Lu

In this article, we give an abstract characterization of the ``identity'' of an operator space $V$ by looking at a quantity $n_{cb}(V,u)$ which is defined in analogue to a well-known quantity in Banach space theory. More precisely, we show…

Operator Algebras · Mathematics 2008-05-27 Xu-Jian Huang , Chi-Keung Ng

In topological equivalence, a bounded linear operator between Banach spaces - we focus on the case of Hilbert spaces - is viewed as only acting linearly and continuously between them qua different spaces with the structure of linear…

Functional Analysis · Mathematics 2021-05-19 Eliahu Levy

We describe a subclass of the class of normal operators on Banach spaces over non-Archimedean fields (A. N. Kochubei, J. Math. Phys. 51 (2010), article 023526) consisting of operators whose properties resemble those of unitary operators. In…

Functional Analysis · Mathematics 2011-02-22 Anatoly N. Kochubei
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