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Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the…

Machine Learning · Computer Science 2023-09-06 Lukáš Novák , Himanshu Sharma , Michael D. Shields

The new class of alternating-conjugate splitting methods is presented and analyzed. They are obtained by concatenating a given composition involving complex coefficients with the same composition but with the complex conjugate coefficients.…

Numerical Analysis · Mathematics 2025-12-19 J. Bernier , S. Blanes , F. Casas , A. Escorihuela-Tomàs

This article presents new methodology for sample-based Bayesian inference when data are partitioned and communication between the parts is expensive, as arises by necessity in the context of "big data" or by choice in order to take…

Methodology · Statistics 2022-11-01 Marc Box

We introduce polynomial couplings, a generalization of probabilistic couplings, to develop an algorithm for the computation of equivalence relations which can be interpreted as a lifting of probabilistic bisimulation to polynomial…

Logic in Computer Science · Computer Science 2021-04-28 Giorgio Bacci , Giovanni Bacci , Kim G. Larsen , Mirco Tribastone , Max Tschaikowski , Andrea Vandin

In this paper, we present splitting algorithms to solve multicomponent transport models with Maxwell-Stefan-diffusion approaches. The multicomponent models are related to transport problems, while we consider plasma processes, in which the…

Numerical Analysis · Mathematics 2023-06-27 Juergen Geiser

The present work provides a comprehensive study of symmetric-conjugate operator splitting methods in the context of linear parabolic problems and demonstrates their additional benefits compared to symmetric splitting methods. Relevant…

Numerical Analysis · Mathematics 2024-01-10 Sergio Blanes , Fernando Casas , Cesáreo González , Mechthild Thalhammer

Variational inference (VI) has become the method of choice for fitting many modern probabilistic models. However, practitioners are faced with a fragmented literature that offers a bewildering array of algorithmic options. First, the…

Machine Learning · Statistics 2018-11-29 Thang D. Bui , Cuong V. Nguyen , Siddharth Swaroop , Richard E. Turner

We present novel coupling schemes for partitioned multi-physics simulation that combine four important aspects for strongly coupled problems: implicit coupling per time step, fast and robust acceleration of the corresponding iterative…

Numerical Analysis · Mathematics 2020-09-21 Benjamin Rüth , Benjamin Uekermann , Miriam Mehl , Philipp Birken , Azahar Monge , Hans-Joachim Bungartz

In the present article, we review a continual effort on generalization of the Trotter formula to higher-order exponential product formulas. The exponential product formula is a good and useful approximant, particularly because it conserves…

Mathematical Physics · Physics 2011-11-10 Naomichi Hatano , Masuo Suzuki

This paper describes an updated exponential Fourier based split-step method that can be applied to a greater class of partial differential equations than previous methods would allow. These equations arise in physics and engineering, a…

Numerical Analysis · Mathematics 2016-06-14 Haider Zia

In this paper, we introduce two parallel extragradient-proximal methods for solving split equilibrium problems. The algorithms combine the extragradient method, the proximal method and the hybrid (outer approximation) method. The weak and…

Optimization and Control · Mathematics 2015-11-10 Dang Van Hieu

We introduce a class of explicit exponential Rosenbrock methods for the time integration of large systems of stiff differential equations. Their application with respect to simulation tasks in the field of visual computing is discussed…

Numerical Analysis · Mathematics 2018-05-23 Vu Thai Luan , Dominik L. Michels

Presenting systems of differential equations in the form of diagrams has become common in certain parts of physics, especially electromagnetism and computational physics. In this work, we aim to put such use of diagrams on a firm…

Mathematical Physics · Physics 2022-06-20 Evan Patterson , Andrew Baas , Timothy Hosgood , James Fairbanks

A local approach to the time integration of PDEs by exponential methods is proposed, motivated by theoretical estimates by A.Iserles on the decay of off-diagonal terms in the exponentials of sparse matrices. An overlapping domain…

Numerical Analysis · Mathematics 2015-05-12 Luca Bonaventura

The proliferation of computing devices has brought about an opportunity to deploy machine learning models on new problem domains using previously inaccessible data. Traditional algorithms for training such models often require data to be…

We consider the numerical solution of partial differential equations with coefficients that are strongly heterogeneous in space. We provide an overview of higher-order localized orthogonal decomposition (LOD) methods for the elliptic…

Numerical Analysis · Mathematics 2026-05-29 Balaje Kalyanaraman , Felix Krumbiegel , Roland Maier , Siyang Wang

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

The solution of many physical evolution equations can be expressed as an exponential of two or more operators acting on initial data. Accurate solutions can be systematically derived by decomposing the exponential in a product form. For…

Computational Physics · Physics 2007-05-23 Siu A. Chin

In this paper we present a novel multiscale splitting approach to solve multiscale Schroedinger equation, which have large different time-scales. The energy potential is based on highly oscillating functions, which are magnitudes faster…

Numerical Analysis · Mathematics 2018-05-31 Juergen Geiser , Amirbahador Nasari

We formulate a well-posedness and approximation theory for a class of generalised saddle point problems. In this way we develop an approach to a class of fourth order elliptic partial differential equations using the idea of splitting into…

Numerical Analysis · Mathematics 2019-04-02 Charles M. Elliott , Hans Fritz , Graham Hobbs