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This paper is concerned with the development and testing of advanced time-stepping methods suited for the integration of time-accurate, real-world applications of computational fluid dynamics (CFD). The performance of several time…

Computational Engineering, Finance, and Science · Computer Science 2017-10-03 Arash Sarshar , Paul Tranquilli , Brent Pickering , Andrew McCall , Adrian Sandu , Christopher J. Roy

In this paper, we address the full discretization of Friedrichs' systems with a two-field structure, such as Maxwell's equations or the acoustic wave equation in div-grad form, cf. [14]. We focus on a discontinuous Galerkin space…

Numerical Analysis · Mathematics 2025-03-10 Marlis Hochbruck , Malik Scheifinger

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods (MCMC). Our results can be used…

Applications · Statistics 2017-10-03 Christos Merkatas , Konstantinos Kaloudis , Spyridon J. Hatjispyros

Variational time discretization schemes are getting of increasing importance for the accurate numerical approximation of transient phenomena. The applicability and value of mixed finite element methods (MFEM) in space for simulating…

Numerical Analysis · Mathematics 2016-12-06 Markus Bause , Florin A. Radu , Uwe Köcher

This paper is dedicated to the presentation and the analysis of a numerical scheme for forward-backward SDEs of the McKean-Vlasov type, or equivalently for solutions to PDEs on the Wasserstein space. Because of the mean field structure of…

Probability · Mathematics 2017-03-07 Jean-François Chassagneux , Dan Crisan , François Delarue

This article deals with the numerical resolution of Markovian backward stochastic differential equations (BSDEs) with drivers of quadratic growth with respect to $z$ and bounded terminal conditions. We first show some bound estimates on the…

Probability · Mathematics 2012-01-10 Adrien Richou

We study higher-order space-time variational discretisations for modeling complex processes in porous media that include fluid and structure interactions which are of fundamental importance in many engineering fields with applications in…

Numerical Analysis · Mathematics 2018-05-03 Uwe Köcher , Markus Bause

Single-stage or single-step high-order temporal discretizations of partial differential equations (PDEs) have shown great promise in delivering high-order accuracy in time with efficient use of computational resources. There has been much…

Numerical Analysis · Mathematics 2021-03-02 Youngjun Lee , Dongwook Lee , Adam Reyes

The space of images can be equipped with a Riemannian metric measuring both the cost of transport of image intensities and the variation of image intensities along motion lines. The resulting metamorphosis model was introduced and analyzed…

Numerical Analysis · Mathematics 2017-05-15 Alexander Effland , Martin Rumpf , Florian Schäfer

The recently proposed numerical algorithm, deep BSDE method, has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations (FBSDEs) and parabolic partial differential equations (PDEs). This…

Probability · Mathematics 2022-03-10 Jiequn Han , Jihao Long

In this work we consider time series with a finite number of discrete point changes. We assume that the data in each segment follows a different probability density functions (pdf). We focus on the case where the data in all segments are…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ali Mohammad-Djafari , Olivier Feron

Complex dynamic systems can be investigated by fitting mechanistic stochastic dynamic models to time series data. In this context, commonly used Monte Carlo inference procedures for model selection and parameter estimation quickly become…

Methodology · Statistics 2025-11-24 Jesse Wheeler , Aaron J. Abkemeier , Edward L. Ionides

Bayesian approaches developed to solve the optimal design of sequential experiments are mathematically elegant but computationally challenging. Recently, techniques using amortization have been proposed to make these Bayesian approaches…

Machine Learning · Computer Science 2022-06-20 Tom Blau , Edwin V. Bonilla , Iadine Chades , Amir Dezfouli

Complex dynamical systems are used for predictions in many domains. Because of computational costs, models are truncated, coarsened, or aggregated. As the neglected and unresolved terms become important, the utility of model predictions…

Machine Learning · Computer Science 2021-08-19 Abhinav Gupta , Pierre F. J. Lermusiaux

Multi-state models are frequently applied for representing processes evolving through a discrete set of state. Important classes of multi-state models arise when transitions between states may depend on the time since entry into the current…

Methodology · Statistics 2022-02-28 Rosario Barone , Andrea Tancredi

Adiabatic quantum computing is a general framework for preparing eigenstates of Hamiltonians on quantum devices. However, its digital implementation requires an efficient Hamiltonian simulation subroutine, which may introduce extra…

Quantum Physics · Physics 2025-09-03 Dong An , Pedro C. S. Costa , Dominic W. Berry

This paper is part of a program to combine a staggered time and staggered spatial discretization of continuum mechanics problems so that any property of the continuum that is proved using vector calculus can be proven in an analogous way…

Numerical Analysis · Mathematics 2019-01-15 Stanly L. Steinberg

This work proposes a discretization of the acoustic wave equation with possibly oscillatory coefficients based on a superposition of discrete solutions to spatially localized subproblems computed with an implicit time discretization. Based…

Numerical Analysis · Mathematics 2024-03-11 Dietmar Gallistl , Roland Maier

Modelling the process of recombination leads to a large coupled nonlinear dynamical system. Here, we consider a particular case of recombination in {\em discrete} time, allowing only for {\em single crossovers}. While the analogous dynamics…

Populations and Evolution · Quantitative Biology 2011-01-12 Ute von Wangenheim , Ellen Baake , Michael Baake

This article is concerned with the discretisation of the Stokes equations on time-dependent domains in an Eulerian coordinate framework. Our work can be seen as an extension of a recent paper by Lehrenfeld & Olshanskii [ESAIM: M2AN,…

Numerical Analysis · Mathematics 2020-12-02 Erik Burman , Stefan Frei , Andre Massing