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In this paper invariant subspace method has been employed for solving linear and non-linear fractional partial differential equations involving Caputo derivative. A variety of illustrative examples are solved to demonstrate the…

Analysis of PDEs · Mathematics 2017-04-18 Sangita Choudhary , Varsha Daftardar-Gejji

The accurate assembly of the system matrix is an important step in any code that solves partial differential equations on a mesh. We either explicitly set up a matrix, or we work in a matrix-free environment where we have to be able to…

Mathematical Software · Computer Science 2020-06-19 Charles D. Murray , Tobias Weinzierl

We examine an analytic variational inference scheme for the Gaussian Process State Space Model (GPSSM) - a probabilistic model for system identification and time-series modelling. Our approach performs variational inference over both the…

Machine Learning · Statistics 2018-12-11 Alessandro Davide Ialongo , Mark van der Wilk , Carl Edward Rasmussen

In this work we present a new simple but efficient scheme - Subsquares approach - for development of algorithms for enclosing the solution set of overdetermined interval linear systems. We are going to show two algorithms based on this…

Numerical Analysis · Computer Science 2013-05-07 Jaroslav Horáček , Milan Hladík

Time-parallel algorithms seek greater concurrency by decomposing the temporal domain of a Partial Differential Equation (PDE), providing possibilities for accelerating the computation of its solution. While parallelisation in time has…

Numerical Analysis · Mathematics 2021-04-20 Federico Danieli , Scott MacLachlan

We develop a stochastic algorithm for independent component analysis that incorporates multi-trial supervision, which is available in many scientific contexts. The method blends a proximal gradient-type algorithm in the space of invertible…

Machine Learning · Computer Science 2025-08-29 Ronak Mehta , Mateus Piovezan Otto , Noah Stanis , Azadeh Yazdan-Shahmorad , Zaid Harchaoui

We propose some numerical schemes for forward-backward stochastic differential equations (FBSDEs) based on a new fundamental concept of transposition solutions. These schemes exploit time-splitting methods for the variation of constants…

Numerical Analysis · Mathematics 2018-05-01 Kazufumi Ito , Yufei Zhang , Jun Zou

A nonlinear adaptive procedure for optimising both the schemes in time and space is proposed in view of increasing the numerical efficiency and reducing the computational time. The method is based on a four-parameter family of schemes we…

Numerical Analysis · Mathematics 2021-01-05 Maria T. Malheiro , Gaspar J. Machado , Stéphane Clain

Accelerated proximal gradient methods have recently been developed for solving quasi-static incremental problems of elastoplastic analysis with some different yield criteria. It has been demonstrated through numerical experiments that these…

Optimization and Control · Mathematics 2020-11-13 Yoshihiro Kanno

The parareal algorithm is known to allow for a significant reduction in wall clock time for accurate numerical solutions by parallelising across the time dimension. We present and test a micro-macro version of parareal, in which the fine…

Numerical Analysis · Mathematics 2019-12-20 Tony Lelièvre , Frédéric Legoll , Keith Myerscough , Giovanni Samaey

The Poisson-Nernst-Planck (PNP) equations are one of the most effective model for describing electrostatic interactions and diffusion processes in ion solution systems, and have been widely used in the numerical simulations of biological…

Numerical Analysis · Mathematics 2023-12-19 Yang Liu , Shi Shu , Ying Yang

In this paper, a novel parallel hybrid iterative method is proposed for finding a common element of the set of solutions of a system of equilibrium problems, the set of solutions of variational inequalities for inverse strongly monotone…

Optimization and Control · Mathematics 2015-10-28 Dang Van Hieu

The accuracy of solving partial differential equations (PDEs) on coarse grids is greatly affected by the choice of discretization schemes. In this work, we propose to learn time integration schemes based on neural networks which satisfy…

Numerical Analysis · Mathematics 2023-10-17 Xinxin Yan , Zhideng Zhou , Xiaohan Cheng , Xiaolei Yang

We consider the coupled system of equations that describe flow in fractured porous media. To describe such types of problems, multicontinuum and multiscale approaches are used. Because in multicontinuum models, the permeability of each…

Numerical Analysis · Mathematics 2023-05-31 Maria Vasilyeva

With steadily increasing parallelism for high-performance architectures, simulations requiring a good strong scalability are prone to be limited in scalability with standard spatial-decomposition strategies at a certain amount of parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-01 Martin Schreiber , Adam Peddle , Terry Haut , Beth Wingate

Numerical solutions of hyperbolic partial differential equations(PDEs) are ubiquitous in science and engineering. Method of lines is a popular approach to discretize PDEs defined in spacetime, where space and time are discretized…

Mathematical Software · Computer Science 2020-11-24 Milinda Fernando , Hari Sundar

In [Heimann, Lehrenfeld, Preu{\ss}, SIAM J. Sci. Comp. 45(2), 2023, B139 - B165] new geometrically unfitted space-time Finite Element methods for partial differential equations posed on moving domains of higher-order accuracy in space and…

Numerical Analysis · Mathematics 2025-03-14 Fabian Heimann , Christoph Lehrenfeld

In this paper, a mixed high order finite difference scheme-Pad\'{e} approximation method is applied to obtain numerical solution of the Riesz fractional advection-dispersion equation. This method is based on the high order finite difference…

Numerical Analysis · Mathematics 2021-05-26 Sohrab Valizadeh , Abdollah Borhanifar

Computational methods for fractional differential equations exhibit essential instability. Even a minor modification of the coefficients or other entry data may switch good results to the divergent. The goal of this paper is to suggest the…

Numerical Analysis · Mathematics 2021-12-20 P. B. Dubovski , J. A. Slepoi

We examine what is an efficient and scalable nonlinear solver, with low work and memory complexity, for many classes of discretized partial differential equations (PDEs) - matrix-free Full multigrid (FMG) with a Full Approximation Storage…

Numerical Analysis · Mathematics 2023-06-07 Mark F. Adams