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Many models require integrals of high-dimensional functions: for instance, to obtain marginal likelihoods. Such integrals may be intractable, or too expensive to compute numerically. Instead, we can use the Laplace approximation (LA). The…

Methodology · Statistics 2024-11-05 Shaun McDonald , David Campbell

Statistical applications often involve the calculation of intractable multidimensional integrals. The Laplace formula is widely used to approximate such integrals. However, in high-dimensional or small sample size problems, the shape of the…

Computation · Statistics 2016-12-30 Erlis Ruli , Nicola Sartori , Laura Ventura

Although much research has been devoted to the problem of restoring Poissonian images, namely in the fields of medical and astronomical imaging, applying the state of the art regularizers (such as those based on wavelets or total variation)…

Optimization and Control · Mathematics 2009-05-01 Mario A. T. Figueiredo , Jose M. Bioucas-Dias

We propose a method to obtain the equilibrium distribution for positions and velocities of a one-dimensional particle via time-averaging and Laplace transformations. We apply it to the case of a damped harmonic oscillator in contact with a…

Statistical Mechanics · Physics 2009-11-11 D. O. Soares-Pinto , W. A. M. Morgado

Laplace interpolation is a popular approach in image inpainting using partial differential equations. The classic approach considers the Laplace equation with mixed boundary conditions. Recently a more general formulation has been proposed…

Analysis of PDEs · Mathematics 2018-01-30 Laurent Hoeltgen , Andreas Kleefeld , Isaac Harris , Michael Breuß

In this paper, we denoise a given noisy image by minimizing a smoothness promoting function over a set of local similarity measures which compare the mean of the given image and some candidate image on a large collection of subboxes. The…

Optimization and Control · Mathematics 2024-06-24 Christian Kanzow , Fabius Krämer , Patrick Mehlitz , Gerd Wachsmuth , Frank Werner

Finding the optimal design of experiments in the Bayesian setting typically requires estimation and optimization of the expected information gain functional. This functional consists of one outer and one inner integral, separated by the…

Numerical Analysis · Mathematics 2024-11-26 Arved Bartuska , Luis Espath , Raúl Tempone

Inpainting based image compression approaches, especially linear and non-linear diffusion models, are an active research topic for lossy image compression. The major challenge in these compression models is to find a small set of…

Computer Vision and Pattern Recognition · Computer Science 2014-05-12 Yunjin Chen , René Ranftl , Thomas Pock

We study approximations to the Moreau envelope -- and infimal convolutions more broadly -- based on Laplace's method, a classical tool in analysis which ties certain integrals to suprema of their integrands. We believe the connection…

Optimization and Control · Mathematics 2024-06-05 Ryan J. Tibshirani , Samy Wu Fung , Howard Heaton , Stanley Osher

In this paper, we develop a sliding method for the fractional Laplacian. We first obtain the key ingredients needed in the sliding method either in a bounded domain or in the whole space, such as narrow region principles and maximum…

Analysis of PDEs · Mathematics 2019-12-03 Leyun Wu , Wenxiong Chen

A spectral method is considered for approximating the fractional Laplacian and solving the fractional Poisson problem in 2D and 3D unit balls. The method is based on the explicit formulation of the eigenfunctions and eigenvalues of the…

Numerical Analysis · Mathematics 2018-12-21 Kailai Xu , Eric Darve

This is not a new result. Purpose of this work is to describe a method to search the analytical expression of the general real solution of the two-dimensional Laplace differential equation. This thing is not easy to find in scientific…

Analysis of PDEs · Mathematics 2009-10-02 Gianluca Argentini

Inference by means of mathematical modeling from a collection of observations remains a crucial tool for scientific discovery and is ubiquitous in application areas such as signal compression, imaging restoration, and supervised machine…

Numerical Analysis · Mathematics 2022-07-19 Matthias Chung , Rosemary Renaut

In this paper, we resort to the Laplace transform method in order to show its efficiency when approaching some types of fractional differential equations. In particular, we present some applications of such methods when applied to possible…

Mathematical Physics · Physics 2015-09-09 Fabio G. Rodrigues , Edmundo C. Oliveira

This article develops, and describes how to use, results concerning disintegrations of Poisson random measures. These results are fashioned as simple tools that can be tailor-made to address inferential questions arising in a wide range of…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

In this paper, we introduce a novel semi-analytical method for solving a broad class of initial value problems involving differential, integro-differential, and delay equations, including those with fractional and variable-order…

Numerical Analysis · Mathematics 2025-10-02 Mohamed Mostafa

This paper describes a general formalism for obtaining localized solutions to a class of problems in mathematical physics, which can be recast as variational optimization problems. This class includes the important cases of Schr\"odinger's…

Numerical Analysis · Mathematics 2014-03-05 Vidvuds Ozoliņš , Rongjie Lai , Russel Caflisch , Stanley Osher

In the present work we discuss how to address the solution of electrostatic problems, in professional cycle, using Green's functions and the Poisson's equation. By using this procedure, it was possible to verify its relation with the method…

Physics Education · Physics 2021-04-20 Glauco Cohen Ferreira Pantoja , Walace S. Elias

For the stochastic heat equation with multiplicative noise we consider the problem of estimating the diffusivity parameter in front of the Laplace operator. Based on local observations in space, we first study an estimator that was derived…

Statistics Theory · Mathematics 2024-02-22 Josef Janák , Markus Reiß

Many imaging problems require solving an inverse problem that is ill-conditioned or ill-posed. Imaging methods typically address this difficulty by regularising the estimation problem to make it well-posed. This often requires setting the…

Methodology · Statistics 2020-08-17 Ana F. Vidal , Valentin De Bortoli , Marcelo Pereyra , Alain Durmus
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