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The main objective of this paper is to extend Morse-Forman theory to vector-valued functions. This is mostly motivated by the need to develop new tools and methods to compute multiparameter persistence. To generalize the theory, in addition…

Geometric Topology · Mathematics 2024-05-17 Guillaume Brouillette , Madjid Allili , Tomasz Kaczynski

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

The generic chaining method provides a sharp description of the suprema of many random processes in terms of the geometry of their index sets. The chaining functionals that arise in this theory are however notoriously difficult to control…

Probability · Mathematics 2018-06-22 Ramon van Handel

We propose a framework for learning maps between probability distributions that broadly generalizes the time dynamics of flow and diffusion models. To enable this, we generalize stochastic interpolants by replacing the scalar time variable…

Machine Learning · Computer Science 2026-02-26 Hugo Negrel , Florentin Coeurdoux , Michael S. Albergo , Eric Vanden-Eijnden

In CAGD the design of a surface that interpolates an arbitrary quadrilateral mesh is definitely a challenging task. The basic requirement is to satisfy both criteria concerning the regularity of the surface and aesthetic concepts. With…

Numerical Analysis · Mathematics 2016-01-08 Michele Antonelli , Carolina Vittoria Beccari , Giulio Casciola

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

Multivariate functions emerge naturally in a wide variety of data-driven models. Popular choices are expressions in the form of basis expansions or neural networks. While highly effective, the resulting functions tend to be hard to…

Machine Learning · Statistics 2022-06-15 Jan Decuyper , Koen Tiels , Siep Weiland , Mark C. Runacres , Johan Schoukens

The final step of most large-scale structure analyses involves the comparison of power spectra or correlation functions to theoretical models. It is clear that the theoretical models have parameter dependence, but frequently the…

Cosmology and Nongalactic Astrophysics · Physics 2016-01-13 Martin White , Nikhil Padmanabhan

Extended real-valued functions are often used in optimization theory, but in different ways for infimum problems and for supremum problems. We present an approach to extended real-valued functions that works for all types of problems and…

Optimization and Control · Mathematics 2018-06-11 Petra Weidner

Our previous work [1] constructed, in three-dimensional momentum space, a manifestly crossing symmetric basis for scalar conformal four-point functions, based on the factorization property proposed by Polyakov. This work extends this…

High Energy Physics - Theory · Physics 2020-01-08 Hiroshi Isono , Toshifumi Noumi , Gary Shiu

Cocompactness is a useful weaker counterpart of compactness in the study of imbeddings between function spaces. In this paper we show that subcritical continuous imbeddings of fractional Sobolev spaces and Besov spaces over \mathbb{R}^{N}…

Analysis of PDEs · Mathematics 2011-09-30 Michael Cwikel , Kyril Tintarev

This paper is concerned with applications of the theory of approximation and interpolation based on compensated convex transforms developed in [K. Zhang, E. Crooks, A. Orlando, Compensated convexity methods for approximations and…

Metric Geometry · Mathematics 2018-09-11 Kewei Zhang , Elaine Crooks , Antonio Orlando

This study introduces a procedure to obtain general expressions, $y = f(x)$, subject to linear constraints on the function and its derivatives defined at specified values. These constrained expressions can be used describe functions with…

Optimization and Control · Mathematics 2017-05-18 Daniele Mortari

Within the new concept of a local iterated function system (local IFS), we consider a class of attractors of such IFSs, namely those that are graphs of functions. These new functions are called local fractal functions and they extend and…

Functional Analysis · Mathematics 2014-08-28 Peter Massopust

Motivated by a recent result which identifies in the special setting of the 2-adic group the Besov space $\dot{B}^{1,\infty}_{1}(\mathbb{Z}_2)$ with $BV(\mathbb{Z}_2)$, the space of function of bounded variation, we study in this article…

Analysis of PDEs · Mathematics 2011-04-20 Diego Chamorro

The main purpose of this paper is to construct not only generating functions of the new approach Genocchi type numbers and polynomials but also interpolation function of these numbers and polynomials which are related to a, b, c arbitrary…

Number Theory · Mathematics 2018-11-19 Burak Kurt , Yilmaz Simsek

We present a new and general framework for convolutional neural network operations on spherical (or omnidirectional) images. Our approach represents the surface as a graph of connected points that doesn't rely on a particular sampling…

Computer Vision and Pattern Recognition · Computer Science 2022-10-20 David Hart , Michael Whitney , Bryan Morse

In this paper, we use some standard numerical techniques to approximate the hypergeometric function $$ {}_2F_1[a,b;c;x]=1+\frac{ab}{c}x+\frac{a(a+1)b(b+1)}{c(c+1)}\frac{x^2}{2!}+\cdots $$ for a range of parameter triples $(a,b,c)$ on the…

Numerical Analysis · Mathematics 2017-07-26 Hina Manoj Arora , Swadesh Kumar Sahoo

In this paper, we consider certain topological properties along with certain types of mappings on these spaces defined by the notion of ideal convergence. In order to do that, we primarily follow in the footsteps of the earlier studies of…

General Topology · Mathematics 2023-01-03 Pratulananda Das , Upasana Samanta , Shou Lin

Decomposition spaces are a class of function spaces constructed out of well-behaved coverings and partitions of unity of a set. The structure of the covering of the set determines the properties of the decomposition space. Besov spaces,…

Functional Analysis · Mathematics 2019-04-03 Eirik Berge , Franz Luef