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Neural ordinary differential equations (NODEs) is an invertible neural network architecture promising for its free-form Jacobian and the availability of a tractable Jacobian determinant estimator. Recently, the representation power of NODEs…

Machine Learning · Computer Science 2020-12-07 Takeshi Teshima , Koichi Tojo , Masahiro Ikeda , Isao Ishikawa , Kenta Oono

We obtain matching direct and inverse theorems for the degree of weighted $L_p$-approximation by polynomials with the Jacobi weights $(1-x)^\alpha (1+x)^\beta$. Combined, the estimates yield a constructive characterization of various…

Classical Analysis and ODEs · Mathematics 2017-10-17 Kirill A. Kopotun , Dany Leviatan , Igor A. Shevchuk

Universal approximation theorems provide a mathematical explanation for the expressive power of neural networks. They assert that, under mild conditions on the activation function, feedforward neural networks are dense in broad function…

Machine Learning · Computer Science 2026-05-21 Soumendu Sundar Mukherjee , Himasish Talukdar

This paper establishes a comprehensive theory of geometric rough paths for mixed fractional Brownian motion (MFBM) and its generalized multi-component extensions. We prove that for a generalized MFBM of the form $M_t^H(a) = \sum_{k=1}^N a_k…

Probability · Mathematics 2025-11-25 Atef Lechiheb

Let $U\subseteq\mathbb{R}^d$ be open and convex. We prove that every (not necessarily Lipschitz or strongly) convex function $f:U\to\mathbb{R}$ can be approximated by real analytic convex functions, uniformly on all of $U$. We also show…

Differential Geometry · Mathematics 2014-10-24 Daniel Azagra

We study universal approximation of continuous functionals on compact subsets of products of Hilbert spaces. We prove that any such functional can be uniformly approximated by models that first take finitely many continuous linear…

Machine Learning · Computer Science 2026-02-04 Andrey Krylov , Maksim Penkin

A geometric p-rough path can be seen to be a genuine path of finite p-variation with values in a Lie group equipped with a natural distance. The group and its distance lift (R^{d},+,0) and its Euclidean distance. This approach allows us to…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

We propose two signature-based methods to solve the optimal stopping problem - that is, to price American options - in non-Markovian frameworks. Both methods rely on a global approximation result for $L^p-$functionals on rough path-spaces,…

Mathematical Finance · Quantitative Finance 2025-02-10 Christian Bayer , Luca Pelizzari , John Schoenmakers

We find asymptotic equalities for exact upper bounds of approximations by Fourier sums in uniform metric on classes of $2\pi$-periodic functions, representable in the form of convolutions of functions $\varphi$, which belong to unit balls…

Classical Analysis and ODEs · Mathematics 2016-03-08 A. S. Serdyuk , T. A. Stepaniuk

The density of polynomials in a weighted space of infinitely differentiable functions in a multidimensional real space is proved under minimal conditions on weight functions and on differences between weight functions. We apply this result…

Classical Analysis and ODEs · Mathematics 2007-05-23 P. V. Fedotova , I. Kh. Musin

This survey paper contains a detailed self-contained introduction to Korovkin-type theorems and to some of their applications concerning the approximation of continuous functions as well as of L^p-functions, by means of positive linear…

Classical Analysis and ODEs · Mathematics 2010-09-15 Francesco Altomare

We generalize the classical Bernstein theorem concerning the constructive description of classes of functions uniformly continuous on the real line. The approximation of continuous bounded functions by entire functions of exponential type…

Complex Variables · Mathematics 2008-03-11 Vladimir Andrievskii

This paper considers the orthogonal expansion of the fractional Brownian motion relative to the Legendre polynomials. Such an expansion has not only theoretical but also practical interest, since it can be applied to approximate and…

Probability · Mathematics 2026-01-13 Konstantin A. Rybakov

We generalize a classical result by A.Macintyre and W.Rogosinski on best $H^p$--approximation in $L^p$ of rational functions. For each inner function $\theta$ we give a description of $H^p$--badly approximable functions in $\bar \theta…

Complex Variables · Mathematics 2013-09-26 R. V. Bessonov

We study approximation by arbitrary linear combinations of $n$ translates of a single function of periodic functions. We construct some methods of this approximation for functions in a class induced by the convolution with a given function,…

Numerical Analysis · Mathematics 2017-03-01 Dinh Dũng , Charles A. Micchelli , Vu Nhat Huy

We prove several universal approximation results at minimal or near-minimal width for approximation of $L^p(\mathbb{R}^{d_x}, \mathbb{R}^{d_y})$ and $C^0(\mathbb{R}^{d_x}, \mathbb{R}^{d_y})$ on compact sets. Our approach uses a unified…

Neural and Evolutionary Computing · Computer Science 2025-12-29 Dennis Rochau , Robin Chan , Hanno Gottschalk

We obtain new equitightness and $C([0,T];L^p(\mathbb{R}^N))$-convergence results for finite-difference approximations of generalized porous medium equations of the form $$ \partial_tu-\mathfrak{L}[\varphi(u)]=g\qquad\text{in…

Analysis of PDEs · Mathematics 2023-02-03 Félix del Teso , Jørgen Endal , Espen R. Jakobsen

Approximations of the image and integral funnel of the closed ball of the space $L_p,$ $p>1,$ under Urysohn type integral operator are considered. The closed ball of the space $L_p,$ $p>1,$ is replaced by the set consisting of a finite…

Functional Analysis · Mathematics 2021-07-20 Anar Huseyin , Nesir Huseyin , Khalik G. Guseinov

We study approximation by arbitrary linear combinations of $n$ translates of a single function of periodic functions. We construct some linear methods of this approximation for univariate functions in the class induced by the convolution…

Numerical Analysis · Mathematics 2021-11-05 Dinh Dũng , Vu Nhat Huy

A theory of differential equations driven by a non-differentiable path has recently been developed by Lyons. We develop an alternative approach to this theory, using (modified Euler approximations), and investigate its applicability to…

Probability · Mathematics 2007-10-04 A. M. Davie