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Related papers: On multi-dimensional sampling and interpolation

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In this work, we study superconvergence properties for some high-order orthogonal polynomial interpolations.The results are two-folds: When interpolating function values, we identify those points where the first and second derivatives of…

Numerical Analysis · Mathematics 2012-04-27 Zhimin Zhang

In this work, we study the Hermite interpolation on $n$-dimensional non-equally spaced, rectilinear grids over a field $\Bbbk $ of characteristic zero, given the values of the function at each point of the grid and the partial derivatives…

The Gaussian Correlation Conjecture states that for any two symmetric, convex sets in n-dimensional space and for any centered, Gaussian measure on that space, the measure of the intersection is greater than or equal to the product of the…

Probability · Mathematics 2016-09-06 Gideon Schechtman , Thomas Schlumprecht , Joel Zinn

The CLEAN algorithm, widely used in radio interferometry for the deconvolution of radio images, performs well only if the raw radio image (dirty image) is, to good approximation, a simple convolution between the instrumental point-spread…

Instrumentation and Methods for Astrophysics · Physics 2015-05-28 I. M. Stewart , D. M. Fenech , T. W. B. Muxlow

The Empirical Interpolation Method (EIM) is a greedy procedure that constructs approximate representations of two-variable functions in separated form. In its classical presentation, the two variables play a non-symmetric role. In this…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Alexandre Ern , Tony Lelièvre

As the vocabulary size of modern word-based language models becomes ever larger, many sampling-based training criteria are proposed and investigated. The essence of these sampling methods is that the softmax-related traversal over the…

Computation and Language · Computer Science 2021-06-18 Yingbo Gao , David Thulke , Alexander Gerstenberger , Khoa Viet Tran , Ralf Schlüter , Hermann Ney

Based on the variable Hilbert scale interpolation inequality bounds for the error of regularisation methods are derived under range inclusions. In this context, new formulae for the modulus of continuity of the inverse of bounded operators…

Numerical Analysis · Mathematics 2010-05-24 Markus Hegland , Bernd Hofmann

Standard interpolation techniques are implicitly based on the assumption that the signal lies on a homogeneous domain. In this letter, the proposed interpolation method instead exploits prior information about domain inhomogeneity,…

Classical Analysis and ODEs · Mathematics 2017-04-14 Hamid Behjat , Zafer Doğan , Dimitri Van De Ville , Leif Sörnmo

Given a finite number of samples of a continuous set-valued function F, mapping an interval to compact subsets of the real line, we develop good approximations of F, which can be computed efficiently.

Numerical Analysis · Mathematics 2022-09-01 Qusay Muzaffar , Nira Dyn , David Levin

The problem of multivariate exponential analysis or sparse interpolation has received a lot of attention, especially with respect to the number of samples required to solve it unambiguously. In this paper we show how to bring the number of…

Numerical Analysis · Mathematics 2017-10-26 Annie Cuyt , Wen-shin Lee

We investigate stochastic interpolation, a recently introduced framework for high dimensional sampling which bears many similarities to diffusion modeling. Stochastic interpolation generates a data sample by first randomly initializing a…

Statistics Theory · Mathematics 2025-10-28 Mara Daniels

Scaling limits of critical percolation models show major differences between low and high dimensional models. The article discusses the formulation of the continuum limit for the former case. A mathematical framework is proposed for the…

Statistical Mechanics · Physics 2009-09-25 Michael Aizenman

The percolation threshold for flow or conduction through voids surrounding randomly placed spheres is rigorously calculated. With large scale Monte Carlo simulations, we give a rigorous continuum treatment to the geometry of the…

Disordered Systems and Neural Networks · Physics 2012-08-02 D. J. Priour

Consider long-range Bernoulli percolation on $\mathbb{Z}^d$ in which we connect each pair of distinct points $x$ and $y$ by an edge with probability $1-\exp(-\beta\|x-y\|^{-d-\alpha})$, where $\alpha>0$ is fixed and $\beta\geq 0$ is a…

Probability · Mathematics 2022-11-23 Tom Hutchcroft

The Patterson-Sullivan construction is proved almost surely to recover a Bergman function from its values on a random discrete subset sampled with the determinantal point process induced by the Bergman kernel on the unit ball $\mathbb{D}_d$…

Complex Variables · Mathematics 2021-01-26 Alexander I. Bufetov , Yanqi Qiu

A statistical inference method is developed and tested for pairwise interacting systems whose degrees of freedom are continuous angular variables, such as planar spins in magnetic systems or wave phases in optics and acoustics. We…

Statistical Mechanics · Physics 2015-06-15 P. Tyagi , A. Pagnani , F. Antenucci , M. Ibáñez Berganza , L. Leuzzi

We study non-stationary averaging processes, where each term of a sequence is a weighted average of previous terms, namely $a_{n+1} = \sum_{j=1}^n p_n(j) a_j$. Our results extend classical theory in two distinct regimes. First, we prove a…

Probability · Mathematics 2026-03-18 Saba Lepsveridze , Elchanan Mossel

The modern definition of optical coherence highlights a frequency dependent function based on a matrix of spectra and cross-spectra. Due to general properties of matrices, such a function is invariant in changes of basis. In this article,…

Optics · Physics 2016-03-09 Bernard Lacaze

We prove a limit theorem for the the maximal interpoint distance (also called the diameter) for a sample of n i.i.d. points in the unit ball of dimension 2 or more. The exact form of the limit distribution and the required normalisation are…

Probability · Mathematics 2007-05-23 Michael Mayer , Ilya Molchanov

We develop a new approximation theory for linear and quadratic interpolation models, suitable for use in convex-constrained derivative-free optimization (DFO). Most existing model-based DFO methods for constrained problems assume the…

Optimization and Control · Mathematics 2024-03-25 Lindon Roberts