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The time parallel solution of optimality systems arising in PDE constraint optimization could be achieved by simply applying any time parallel algorithm, such as Parareal, to solve the forward and backward evolution problems arising in the…

Analysis of PDEs · Mathematics 2020-07-27 Martin Gander , Félix Kwok , Julien Salomon

The Fast Fourier Transform is extended to functions on finite graphs whose edges are identified with intervals of finite length. Spectral and pseudospectral methods are developed to solve a wide variety of time dependent partial…

Numerical Analysis · Mathematics 2025-07-11 Robert Carlson

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady…

Numerical Analysis · Mathematics 2012-04-10 Stéphane Descombes , Max Duarte , Thierry Dumont , Violaine Louvet , Marc Massot

In this work, we present an efficient way to decouple the multicontinuum problems. To construct decoupled schemes, we propose Implicit-Explicit time approximation in general form and study them for the fine-scale and coarse-scale space…

Numerical Analysis · Mathematics 2024-04-26 Maria Vasilyeva

This paper presents a new finite difference method, called {\varphi}-FD, inspired by the {\phi}-FEM approach for solving elliptic partial differential equations (PDEs) on general geometries. The proposed method uses Cartesian grids,…

Numerical Analysis · Mathematics 2025-05-28 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

Several recent works have explored stochastic gradient methods for variational inference that exploit the geometry of the variational-parameter space. However, the theoretical properties of these methods are not well-understood and these…

Machine Learning · Statistics 2016-08-15 Mohammad Emtiyaz Khan , Reza Babanezhad , Wu Lin , Mark Schmidt , Masashi Sugiyama

The simulation of systems that act on multiple time scales is challenging. A stable integration of the fast dynamics requires a highly accurate approximation whereas for the simulation of the slow part, a coarser approximation is accurate…

Numerical Analysis · Mathematics 2024-06-21 Sina Ober-Blöbaum , Theresa Wenger , Tobias Gail , Sigrid Leyendecker

In real-time systems, in addition to the functional correctness recurrent tasks must fulfill timing constraints to ensure the correct behavior of the system. Partitioned scheduling is widely used in real-time systems, i.e., the tasks are…

Data Structures and Algorithms · Computer Science 2018-09-13 Jian-Jia Chen , Nikhil Bansal , Samarjit Chakraborty , Georg von der Brüggen

We present multigrid methods for solving elliptic partial differential equations on arbitrary domains using the nodal ghost finite element method, an unfitted boundary approach where the domain is implicitly defined by a level-set function.…

Numerical Analysis · Mathematics 2025-05-09 Hridya Dilip , Armando Coco

The applicability of the Parareal parallel-in-time integration scheme for the solution of a linear, two-dimensional hyperbolic acoustic-advection system, which is often used as a test case for integration schemes for numerical weather…

Computational Engineering, Finance, and Science · Computer Science 2015-10-09 Daniel Ruprecht , Rolf Krause

Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the output of numerical methods. The use of these methods is usually motivated by the fact that they can represent our uncertainty due to…

Computation · Statistics 2018-08-01 Xiaoyue Xi , François-Xavier Briol , Mark Girolami

Due to rapid data growth, statistical analysis of massive datasets often has to be carried out in a distributed fashion, either because several datasets stored in separate physical locations are all relevant to a given problem, or simply to…

Computation · Statistics 2016-02-08 Matthias Katzfuss , Dorit Hammerling

Variational approximation methods have proven to be useful for scaling Bayesian computations to large data sets and highly parametrized models. Applying variational methods involves solving an optimization problem, and recent research in…

Methodology · Statistics 2017-01-13 Victor M. -H. Ong , David J. Nott , Michael S. Smith

We consider problems with multiple linear objectives and linear constraints and use Adjustable Robust Optimization and Polynomial Optimization as tools to approximate the Pareto set with polynomials of arbitrarily large degree. The main…

Optimization and Control · Mathematics 2015-01-13 Bram L. Gorissen , Dick den Hertog

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications.Here we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems.This type…

Computational Geometry · Computer Science 2020-10-01 Camille Coti , David Monniaux , Hang Yu

A linearized numerical scheme is proposed to solve the nonlinear time fractional parabolic problems with time delay. The scheme is based on the standard Galerkin finite element method in the spatial direction, the fractional Crank-Nicolson…

Numerical Analysis · Mathematics 2021-09-10 Lili Li , Mianfu She , Yuanling Niu

This paper is to give an overview of AMG methods for solving large scale systems of equations such as those from the discretization of partial differential equations. AMG is often understood as the acronym of "Algebraic Multi-Grid", but it…

Numerical Analysis · Mathematics 2016-11-11 Jinchao Xu , Ludmil T Zikatanov

In this work, a new parallel dual-grid multiscale approach for CFD-DEM couplings is investigated. Dual- grid multiscale CFD-DEM couplings have been recently developed and successfully adopted in different applications still, an efficient…

Computational Engineering, Finance, and Science · Computer Science 2018-12-26 Gabriele Pozzetti , Hrvoje Jasak , Xavier Besseron , Alban Rousset , Bernhard Peters

Time-parallel methods can reduce the wall clock time required for the accurate numerical solution of differential equations by parallelizing across the time-dimension. In this paper, we present and test the convergence behavior of a…

Numerical Analysis · Mathematics 2025-02-03 Ignace Bossuyt , Giovanni Samaey , Stefan Vandewalle