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We present a general theory for studying the difference analogues of special functions of hypergeometric type on the linear-type lattices, i.e., the solutions of the second order linear difference equation of hypergeometric type on a…

Classical Analysis and ODEs · Mathematics 2014-02-06 R. Alvarez-Nodarse , J. L. Cardoso

The package High-dimensional Metrics (\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence…

Machine Learning · Statistics 2017-09-28 Victor Chernozhukov , Chris Hansen , Martin Spindler

We begin by defining general hypergeometric functions over finite fields and obtaining a finite field analogue of a classical symmetry in their complex counterparts. We give a geometric proof for the symmetry by constructing isomorphisms…

Number Theory · Mathematics 2026-04-22 Akio Nakagawa

Submodular functions have been studied extensively in machine learning and data mining. In particular, the optimization of submodular functions over the integer lattice (integer submodular functions) has recently attracted much interest,…

Machine Learning · Computer Science 2020-06-03 Aytunc Sahin , Yatao Bian , Joachim M. Buhmann , Andreas Krause

Hydrodynamical simulations are the most accurate way to model structure formation in the universe, but they often involve a large number of astrophysical parameters modeling subgrid physics, in addition to cosmological parameters. This…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-05 Benjamin Horowitz , Zarija Lukic

We construct integrable pseudopotentials with an arbitrary number of fields in terms of generalized hypergeometric functions. These pseudopotentials yield some integrable (2+1)-dimensional hydrodynamic type systems. An interesting class of…

Exactly Solvable and Integrable Systems · Physics 2008-05-12 Alexander Odesskii , Vladimir Sokolov

The image subtraction method is a powerful tool to analyze the light variations in crowded fields. This method is able to achieve a nearly optimal differential photometry, even in very dense regions. However, image subtraction is not…

Astrophysics · Physics 2007-05-23 C. Alard

The known Complex Step Derivative (CSD) method allows easy and accurate differentiation up to machine precision of real analytic functions by evaluating them a small imaginary step next to the real number line. The current paper proposes…

Numerical Analysis · Mathematics 2021-06-18 Martin Roelfs , David Dudal , Daan Huybrechs

When studying boundary value problems for some partial differential equations arising in applied mathematics, we often have to study the solution of a system of partial differential equations satisfied by hypergeometric functions and find…

Classical Analysis and ODEs · Mathematics 2020-05-26 Michael Ruzhansky , Anvar Hasanov

Motivated mainly by certain interesting recent extensions of the Gamma, Beta and hypergeometric functions, we introduce here new extensions of the Beta function, hypergeometric and confluent hypergeometric functions. We systematically…

Classical Analysis and ODEs · Mathematics 2015-02-24 R. K. Parmar , P. Chopra , R. B. Paris

A computer-algebra aided method is carried out, for determining geometric objects associated to differential operators that satisfy the elliptic ansatz. This results in examples of Lame curves with double reduction and in the explicit…

Mathematical Physics · Physics 2008-04-24 J. Chris Eilbeck , Victor Z. Enolski , Emma Previato

Motivated by the physical concept of special geometry two mathematical constructions are studied, which relate real hypersurfaces to tube domains and complex Lagrangean cones respectively. Me\-thods are developed for the classification of…

Differential Geometry · Mathematics 2016-09-06 Vicente Cortés

A unifying scheme of classical special functions of hypergeometric type obeying orthogonality or biorthogonality relations is described. It expands the Askey scheme of classical orthogonal polynomials and its $q$-analogue based on the…

Classical Analysis and ODEs · Mathematics 2024-03-26 Vyacheslav P. Spiridonov

The spherical-radial decomposition (SRD) is an efficient method for estimating probabilistic functions and their gradients defined over finite-dimensional elliptical distributions. In this work, we generalize the SRD to infinite stochastic…

Optimization and Control · Mathematics 2026-03-23 Kewei Wang , Georg Stadler

We consider Hilbert-type functions associated with difference (not necessarily inversive) field extensions and systems of algebraic difference equations in the case when the translations are assigned some integer weights. We will show that…

Commutative Algebra · Mathematics 2016-09-28 Alexander Levin

The object recognition is a complex problem in the image processing. Mathematical morphology is Shape oriented operations, that simplify image data, preserving their essential shape characteristics and eliminating irrelevancies. This paper…

Computer Vision and Pattern Recognition · Computer Science 2015-07-28 R. P. Prakash , Keerthana S. Prakash , V. P. Binu

Series containing the digamma function arise when calculating the parametric derivatives of the hypergeometric functions and play a role in evaluation of Feynman diagrams. As these series are typically non-hypergeometric, a few instances…

Classical Analysis and ODEs · Mathematics 2023-04-11 Asena Çetinkaya , Dmitrii Karp

We generalize the known constructions of A-hypergeometric functions. In particular, we show that periods of middle dimension on affine or projective complex algebraic varieties are A-hypergeometric functions of coefficients of polynomial…

Algebraic Geometry · Mathematics 2014-03-20 A. V. Stoyanovsky

Harten's Multiresolution framework has been applied in different contexts, such as in the numerical simulation of PDE with conservation laws or in image compression, showing its flexibility to describe and manipulate the data in a…

Numerical Analysis · Mathematics 2019-09-10 Sergio López-Ureña

First-order automatic differentiation is a ubiquitous tool across statistics, machine learning, and computer science. Higher-order implementations of automatic differentiation, however, have yet to realize the same utility. In this paper I…

Computation · Statistics 2019-01-01 Michael Betancourt
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