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Understanding how agents learn to generalize -- and, in particular, to extrapolate -- in high-dimensional, naturalistic environments remains a challenge for both machine learning and the study of biological agents. One approach to this has…

Machine Learning · Computer Science 2021-06-15 Simon N. Segert , Jonathan D. Cohen

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

In theoretical physics, we sometimes have two perturbative expansions of physical quantity around different two points in parameter space. In terms of the two perturbative expansions, we introduce a new type of smooth interpolating function…

High Energy Physics - Theory · Physics 2015-06-22 Masazumi Honda

The simplest way to obtain continuous interpolation between two points in high dimensional space is to draw a line between them. While previous works focused on the general connectivity between model parameters, we explored linear…

Computation and Language · Computer Science 2022-11-23 Mark Rofin , Nikita Balagansky , Daniil Gavrilov

Interpolation Theory gives techniques for constructing spaces from two initial Banach spaces. We provide several conditions under which the restriction of a holomorphic map $f:X_0+X_1 \rightarrow Y_0+Y_1$ to the interpolated spaces (using…

Functional Analysis · Mathematics 2017-06-21 Pablo Jiménez-Rodíguez

We provide a general framework to construct fractal interpolation surfaces (FISs) for a prescribed countably infinite data set on a rectangular grid. Using this as a crucial tool, we obtain a parameterized family of bivariate fractal…

Dynamical Systems · Mathematics 2020-10-13 K. K. Pandey , P. Viswanathan

The canonical generalizations of two classical norms on Besov spaces are shown to be equivalent even in the case of non-linear Besov spaces, that is, function spaces consisting of functions taking values in a metric space and equipped with…

Functional Analysis · Mathematics 2024-06-19 Chong Liu , David J. Prömel , Josef Teichmann

This paper proposes a general duality framework for the problem of minimizing a convex integral functional over a space of stochastic processes adapted to a given filtration. The framework unifies many well-known duality frameworks from…

Computational Finance · Quantitative Finance 2010-06-28 Teemu Pennanen

Bessel potential spaces, introduced in the 1960s, are derived through complex interpolation between Lebesgue and Sobolev spaces, making them intermediate spaces of fractional differentiability order. Bessel potential spaces have recently…

Functional Analysis · Mathematics 2025-11-11 José Carlos Bellido , Guillermo García-Sáez

A typical approach to analysing statistical properties of expanding maps is to show spectral gaps of associated transfer operators in adapted function spaces. The classical function spaces for this purpose are H\"older spaces and Sobolev…

Dynamical Systems · Mathematics 2022-03-30 Yushi Nakano , Shota Sakamoto

The interaction between two particles with shape or interaction anisotropy can be modeled using a pairwise potential energy function that depends on their relative position and orientation; however, this function is often challenging to…

Soft Condensed Matter · Physics 2025-03-03 Mohammadreza Fakhraei , Chris A. Kieslich , Michael P. Howard

In this paper, we extend the structure-preserving interpolatory model reduction framework, originally developed for linear systems, to structured bilinear control systems. Specifically, we give explicit construction formulae for the model…

Numerical Analysis · Mathematics 2021-05-17 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

In this paper, we present an interpolation framework for structure-preserving model order reduction of parametric bilinear dynamical systems. We introduce a general setting, covering a broad variety of different structures for parametric…

Numerical Analysis · Mathematics 2021-07-13 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

In the setting of the multidimensional Mellin analysis we introduce moduli of continuity and use them to define Besov-Mellin spaces. We prove that Besov-Mellin spaces are the interpolation spaces (in the sense of J.Peetre) between two…

Functional Analysis · Mathematics 2024-09-09 Isaac Z. Pesenson

Functions in a Sobolev space are approximated directly by piecewise affine interpolation in the norm of the space. The proof is based on estimates for interpolations and does not rely on the density of smooth functions.

Functional Analysis · Mathematics 2014-11-11 Jean Van Schaftingen

In this article, we study the novel concept of non-stationary iterated function systems (IFSs) introduced by Massopust in 2019. At first, using a sequence of different contractive operators, we construct non-stationary $\alpha$-fractal…

Dynamical Systems · Mathematics 2023-03-21 Anarul Islam Mondal , Sangita Jha

We introduce a novel framework for embedding anisotropic variable exponent Sobolev spaces into spaces of anisotropic variable exponent H\"{o}lder-continuous functions within rectangular domains. We establish a foundational approach to…

Functional Analysis · Mathematics 2024-11-21 Nabil Chems Eddine , Dušan D. Repovš

In this paper, Peetre's conjecture about the real interpolation space of Besov space {\bf is solved completely } by using the classification of vertices of cuboids defined by {\bf wavelet coefficients and wavelet's grid structure}.…

Functional Analysis · Mathematics 2024-10-08 Qixiang Yang , Haibo Yang , Bin Zou , Jianxun He

In this paper, by the use of Potential Theory, some representation results for multivariate functions from the Sobolev spaces in terms of the double layer potential and the fundamental solution of Laplace's equation are pointed out.…

Analysis of PDEs · Mathematics 2007-05-23 Florica-Corina Cirstea , Sever Silvestru Dragomir