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Functional decomposition is the process of breaking down a function $f$ into a composition $f=g(f_1,\dots,f_k)$ of simpler functions $f_1,\dots,f_k$ belonging to some class $\mathcal{F}$. This fundamental notion can be used to model…

Computational Complexity · Computer Science 2026-01-14 Mateus de Oliveira Oliveira , Wim Van den Broeck

We show how to get explicit induction formulae for finite group representations, and more generally for rational Green functors, by summing a divergent series over Dwyer's subgroup and centralizer decomposition spaces. This results in…

Group Theory · Mathematics 2019-03-18 Cihan Bahran

We characterize bounded, compact, and Hilbert-Schmidt composition-differentiation operators on weighted Dirichlet spaces. The essential norm is estimated via the asymptotic behavior of a function that involves the generalized Nevanlinna…

Functional Analysis · Mathematics 2026-05-04 Anirban Sen , Somdatta Barik , Kallol paul

This paper proposes a new method based on neural networks for computing the high-dimensional committor functions that satisfy Fokker-Planck equations. Instead of working with partial differential equations, the new method works with an…

Numerical Analysis · Mathematics 2021-05-06 Haoya Li , Yuehaw Khoo , Yinuo Ren , Lexing Ying

I present a partly pedagogic discussion of the Gel'fand-Yaglom formula for the functional determinant of a one-dimensional, second order difference operator, in the simplest settings. The formula is a textbook one in discrete…

Mathematical Physics · Physics 2015-06-03 J. S. Dowker

I relate some coefficients encountered when computing the functional determinants on spheres to the central differentials of nothing. In doing this I use some historic works, in particular transcribing the elegant symbolic formalism of…

Numerical Analysis · Mathematics 2013-05-29 J. S. Dowker

By employing contour integration the derivation of a generalized double finite series involving the Hurwitz-Lerch zeta function is used to derive closed form formulae in terms of special functions. We use this procedure to find special…

Number Theory · Mathematics 2023-09-08 Robert Reynolds

While the definition of a fractional integral may be codified by Riemann and Liouville, an agreed-upon fractional derivative has eluded discovery for many years. This is likely a result of integral definitions including numerous constants…

Classical Analysis and ODEs · Mathematics 2018-10-10 Evan Camrud

Finite volume methods for problems involving second order operators with full diffusion matrix can be used thanks to the definition of a discrete gradient for piecewise constant functions on unstructured meshes satisfying an orthogonality…

Numerical Analysis · Mathematics 2016-08-16 Robert Eymard , Thierry Gallouët , Raphaèle Herbin

In this paper we consider a generalized classical mechanics with fractional derivatives. The generalization is based on the time-clock randomization of momenta and coordinates taken from the conventional phase space. The fractional…

Classical Physics · Physics 2011-11-15 Aleksander Stanislavsky

We present a direct approach for the calculation of functional determinants of the Laplace operator on balls. Dirichlet and Robin boundary conditions are considered. Using this approach, formulas for any value of the dimension, $D$, of the…

High Energy Physics - Theory · Physics 2016-08-15 M. Bordag , B. Geyer , K. Kirsten , E. Elizalde

Although being powerful, the differential transform method yet suffers from a drawback which is how to compute the differential transform of nonlinear non-autonomous functions that can limit its applicability. In order to overcome this…

Classical Analysis and ODEs · Mathematics 2016-12-28 Essam. R. El-Zahar , Abdelhalim Ebaid

We give an introduction to discrete functional analysis techniques for stationary and transient diffusion equations. We show how these techniques are used to establish the convergence of various numerical schemes without assuming…

Numerical Analysis · Mathematics 2016-02-25 Jerome Droniou

We have been working in many aspects of the problem of analyzing, understanding and solving ordinary differential equations (first and second order). As we have extensively mentioned, while working in the Darboux type methods, the most…

Mathematical Physics · Physics 2011-04-27 L. G. S. Duarte , L. A. C. P. da Mota

In this work, the existence of solutions (in a suitable sense) to a family of inclusion systems involving fractional, possibly competing, elliptic operators, fractional convection, and homogeneous Dirichlet boundary conditions is…

Analysis of PDEs · Mathematics 2025-05-13 Jinxia Cen , Salvatore A. Marano , Shengda Zeng

A Dirichlet-type problem is studied for an equation of even order with variable coefficients. A criterion for the uniqueness of a solution is given. The solution is built in the form of a Fourier series. When justifying the convergence of…

Analysis of PDEs · Mathematics 2021-06-01 B. Irgashev

In this paper, we introduce a new second-order directional derivative and a second-order subdifferential of Hadamard type for an arbitrary nondifferentiable function. We derive several second-order optimality conditions for a local and a…

Optimization and Control · Mathematics 2018-05-24 Vsevolod I. Ivanov

The Fourier transform is naturally defined for integrable functrions. Otherwise, it should be stipulated in which sense the Fourier transform is understood. We consider some class of radial and, generally saying, nonintegrable functions.…

funct-an · Mathematics 2008-02-03 Elijah Liflyand

The paper explores the differential inclusion of a special form. It is supposed that the support function of the set in the right-hand side of an inclusion may contain the maximum of the finite number of continuously differentiable (in…

Optimization and Control · Mathematics 2023-05-04 Alexander Fominyh

Functional ANOVA offers a principled framework for interpretability by decomposing a model's prediction into main effects and higher-order interactions. For independent features, this decomposition is well-defined, strongly linked with SHAP…

Machine Learning · Statistics 2026-03-04 Baptiste Ferrere , Nicolas Bousquet , Fabrice Gamboa , Jean-Michel Loubes , Joseph Muré
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