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An adaptive scheme to generate reduced-order models for parametric nonlinear dynamical systems is proposed. It aims to automatize the POD-Greedy algorithm combined with empirical interpolation. At each iteration, it is able to adaptively…

Numerical Analysis · Mathematics 2021-10-13 Sridhar Chellappa , Lihong Feng , Peter Benner

In this work, we propose a class of high order semi-Lagrangian scheme for a general consistent BGK model for inert gas mixtures. The proposed scheme not only fulfills indifferentiability principle, but also asymptotic preserving property,…

Numerical Analysis · Mathematics 2020-12-07 Seung Yeon Cho , Sebastiano Boscarino , Maria Groppi , Giovanni Russo

It has now become customary in the field of numerical relativity to couple high order finite difference schemes to mesh refinement algorithms. To this end, different modifications to the standard Berger-Oliger adaptive mesh refinement…

General Relativity and Quantum Cosmology · Physics 2015-04-29 Bishop Mongwane

This work is devoted to the numerical implementation of the quantum Bhatnagar- Gross-Krook (BGK) model for gas mixtures consisting of classical and quantum particles (fermions, bosons). We consider the model proposed by Bae, Klingenberg,…

Numerical Analysis · Mathematics 2025-02-04 Gi-Chan Bae , Marlies Pirner , Sandra Warnecke

We study the stability of a two-dimensional Lax-Wendroff scheme in a quarter-plane. Following our previous work, we aim here at adapting the energy method in order to study second order extrapolation boundary conditions. We first show on…

Numerical Analysis · Mathematics 2024-05-31 Antoine Benoit , Jean-François Coulombel

In a previous work, we have proposed a method for the analysis of the bounce back boundary condition with the Taylor expansion method in the linear case. In this work two new schemes of modified bounce back are proposed. The first one is…

Numerical Analysis · Mathematics 2019-12-24 François Dubois , Pierre Lallemand , Mohamed Mahdi Tekitek

One goal in Bayesian machine learning is to encode prior knowledge into prior distributions, to model data efficiently. We consider prior knowledge from systems of linear partial differential equations together with their boundary…

Machine Learning · Computer Science 2021-02-16 Markus Lange-Hegermann

We derive a novel framework called Bi-Directional Grid Constrained (BGC) stochastic processes in which the further an Ito diffusion drifts away from the origin, then the further it will be constrained. By making suitable modifications to…

Probability · Mathematics 2021-03-05 A. Taranto , S. Khan , R. Addie

We are interested in numerical algorithms for computing the electrical field generated by a charge distribution localized on scale $\ell$ in an infinite heterogeneous medium, in a situation where the medium is only known in a box of…

Analysis of PDEs · Mathematics 2024-07-24 Jianfeng Lu , Felix Otto , Lihan Wang

In this paper, we consider an accelerated method for solving nonconvex and nonsmooth minimization problems. We propose a Bregman Proximal Gradient algorithm with extrapolation(BPGe). This algorithm extends and accelerates the Bregman…

Optimization and Control · Mathematics 2019-04-26 Xiaoya Zhang , Roberto Barrio , M. Angeles Martinez , Hao Jiang , Lizhi Cheng

The existence and uniqueness of a solution to a generalized Blasius equation with asymptotic boundary conditions are proved. A new numerical approximation method is proposed.

Analysis of PDEs · Mathematics 2011-09-13 Grzegorz Andrzejczak , Magdalena Nockowska-Rosiak , Bogdan Przeradzki

We obtain a new bound for incomplete Gauss sums modulo primes. Our argument falls under the framework of Vinogradov's method which we use to reduce the problem under consideration to bounding the number of solutions to two distinct systems…

Number Theory · Mathematics 2017-06-20 Bryce Kerr

This paper proposes a new second-order symmetric algorithm for solving decoupled forward-backward stochastic differential equations. Inspired by the alternating direction implicit splitting method for partial differential equations, we…

Numerical Analysis · Mathematics 2026-01-16 Wenbo Wang , Guangyan Jia

This paper introduces new methodology to triangulate dynamic Bayesian networks (DBNs) and dynamic graphical models (DGMs). While most methods to triangulate such networks use some form of constrained elimination scheme based on properties…

Artificial Intelligence · Computer Science 2012-12-12 Jeff A. Bilmes , Chris Bartels

We present extended Galerkin neural networks (xGNN), a variational framework for approximating general boundary value problems (BVPs) with error control. The main contributions of this work are (1) a rigorous theory guiding the construction…

Numerical Analysis · Mathematics 2024-12-04 Mark Ainsworth , Justin Dong

Many functions have approximately-known upper and/or lower bounds, potentially aiding the modeling of such functions. In this paper, we introduce Gaussian process models for functions where such bounds are (approximately) known. More…

Machine Learning · Computer Science 2022-10-20 Vu Nguyen , Marc Peter Deisenroth , Michael A. Osborne

In [5] the authors suggested a new algorithm for the numerical approximation of a BSDE by merging the cubature method with the first order discretization developed by [3] and [16]. Though the algorithm presented in [5] compared…

Probability · Mathematics 2010-12-30 Dan Crisan , Konstantinos Manolarakis

We propose an approximation of nonlinear renewal equations by means of ordinary differential equations. We consider the integrated state, which is absolutely continuous and satisfies a delay differential equation. By applying the…

Numerical Analysis · Mathematics 2021-03-23 Francesca Scarabel , Odo Diekmann , Rossana Vermiglio

This paper presents a new approach and methodology to solve the second order one dimensional hyperbolic telegraph equation with Dirichlet and Neumann boundary conditions using the cubic trigonometric B-spline collocation method. The usual…

Numerical Analysis · Mathematics 2017-09-28 Tahir Nazir , Muhammad Abbas , Ahmad Izani Md. Ismail , Ahmad Abd. Majid

We show that a generalised sparse grid combination technique which combines multi-variate extrapolation of finite difference solutions with the standard combination formula lifts a second order accurate scheme on regular meshes to a fourth…

Numerical Analysis · Mathematics 2026-01-08 Julia Muñoz-Echániz , Christoph Reisinger
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