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A deformed differential calculus is developed based on an associative star-product. In two dimensions the Hamiltonian vector fields model the algebra of pseudo-differential operator, as used in the theory of integrable systems. Thus one…

High Energy Physics - Theory · Physics 2020-12-16 I. A. B. Strachan

This article presents two novel adaptive-sparse polynomial dimensional decomposition (PDD) methods for solving high-dimensional uncertainty quantification problems in computational science and engineering. The methods entail global…

Numerical Analysis · Mathematics 2015-06-18 Vaibhav Yadav , Sharif Rahman

In this paper we apply the INTERNODES method to solve second order elliptic problems discretized by Isogeometric Analysis methods on non-conforming multiple patches in 2D and 3D geometries. INTERNODES is an interpolation-based method that,…

Numerical Analysis · Mathematics 2019-10-10 Paola Gervasio , Federico Marini

In this work we propose a simple but effective high order polynomial correction allowing to enhance the consistency of all kind of boundary conditions for the Euler equations (Dirichlet, characteristic far-field and slip-wall), both in 2D…

Numerical Analysis · Mathematics 2022-09-30 Mirco Ciallella , Elena Gaburro , Marco Lorini , Mario Ricchiuto

In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already…

Machine Learning · Computer Science 2017-06-05 Pratik Chaudhari , Adam Oberman , Stanley Osher , Stefano Soatto , Guillaume Carlier

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 Immersed Boundary method is a simple, efficient, and robust numerical scheme for solving PDE in general domains, yet it only achieves first-order spatial accuracy near embedded boundaries. In this paper, we introduce a new high-order…

Numerical Analysis · Mathematics 2016-09-14 David B. Stein , Robert D. Guy , Becca Thomases

High-dimensional partial-differential equations (PDEs) arise in a number of fields of science and engineering, where they are used to describe the evolution of joint probability functions. Their examples include the Boltzmann and…

Numerical Analysis · Mathematics 2018-10-17 A. M. P. Boelens , D. Venturi , D. M. Tartakovsky

We fully generalize a previously-developed computational geometry tool [1] to perform large-scale simulations of arbitrary two-dimensional faceted surfaces $z = h(x,y)$. Our method uses a three-component facet/edge/junction storage model,…

Mathematical Physics · Physics 2011-10-17 Scott A. Norris , Stephen J. Watson

A numerical method for coupled 3D-1D problems with discontinuous solutions at the interfaces is derived and discussed. This extends a previous work on the subject where only continuous solutions were considered. Thanks to properly defined…

Numerical Analysis · Mathematics 2022-03-04 Stefano Berrone , Denise Grappein , Stefano Scialò

Scalar extrapolation and convergence acceleration methods are central tools in numerical analysis for improving the efficiency of iterative algorithms and the summation of slowly convergent series. These methods construct transformed…

Numerical Analysis · Mathematics 2026-02-03 Khalide Jbilou

In this paper, practically computable low-order approximations of potentially high-dimensional differential equations driven by geometric rough paths are proposed and investigated. In particular, equations are studied that cover the linear…

Numerical Analysis · Mathematics 2023-07-03 Martin Redmann , Sebastian Riedel

We introduce Soft Kernel Interpolation (SoftKI), a method that combines aspects of Structured Kernel Interpolation (SKI) and variational inducing point methods, to achieve scalable Gaussian Process (GP) regression on high-dimensional…

Machine Learning · Statistics 2025-09-18 Chris Camaño , Daniel Huang

Discrete exterior calculus (DEC) offers a coordinate-free discretization of exterior calculus especially suited for computations on curved spaces. In this work, we present an extended version of DEC on surface meshes formed by general…

Numerical Analysis · Mathematics 2024-01-30 Lenka Ptackova , Luiz Velho

A method based on orthogonal function series interpolation of the square root probability density to analyze higher dimensional scattered data is presented. The method is targeted for the use-case when the model and/or data are available…

Data Analysis, Statistics and Probability · Physics 2022-03-01 K. Gellerstedt , J. Sjölin

We propose algorithms for solving high-dimensional Partial Differential Equations (PDEs) that combine a probabilistic interpretation of PDEs, through Feynman-Kac representation, with sparse interpolation. Monte-Carlo methods and…

Numerical Analysis · Mathematics 2022-03-25 Marie Billaud-Friess , Arthur Macherey , Anthony Nouy , Clémentine Prieur

We propose a collocation method based on multivariate polynomial splines over triangulation or tetrahedralization for the numerical solution of partial differential equations. We start with a detailed explanation of the method for the…

Numerical Analysis · Mathematics 2023-04-18 Ming-Jun Lai , Jinsil Lee

Accurate and fast 3D imaging of specular surfaces still poses major challenges for state-of-the-art optical measurement principles. Frequently used methods, such as phase-measuring deflectometry (PMD) or shape-from-polarization (SfP), rely…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Jiazhang Wang , Oliver Cossairt , Florian Willomitzer

We study an expansion method for high-dimensional parabolic PDEs which constructs accurate approximate solutions by decomposition into solutions to lower-dimensional PDEs, and which is particularly effective if there are a low number of…

Analysis of PDEs · Mathematics 2016-11-08 Christoph Reisinger , Rasmus Wissmann

We extend a recently developed method to solve semi-linear PDEs to the case of a degenerated diffusion. Being a pure Monte Carlo method it does not suffer from the so called curse of dimensionality and it can be used to solve problems that…

Probability · Mathematics 2018-05-15 Xavier Warin