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We propose a model order reduction approach to speed up the computation of seismograms, i.e. the solution of the seismic wave equation evaluated at a receiver location, for different model parameters. Our approach achieves a reduction of…

Numerical Analysis · Mathematics 2024-06-12 Rhys Hawkins , Muhammad Hamza Khalid , Matthias Schlottbom , Kathrin Smetana

We discuss some aspects of approximating functions on high-dimensional data sets with additive functions or ANOVA decompositions, that is, sums of functions depending on fewer variables each. It is seen that under appropriate smoothness…

Data Structures and Algorithms · Computer Science 2009-11-17 Markus Hegland , Vladimir Pestov

In previous articles, we showed that, based on large-order asymptotic behavior, one can approximate a divergent series via the parametrization of a specific hypergeometric approximant. The analytical continuation is then carried out through…

High Energy Physics - Theory · Physics 2023-08-09 Abouzeid M. Shalaby

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

We present a construction of a non-hermitian fermionic Lagrangian which has a second-order kinetic term. Despite the non-hermicity of the latter, the theory is unitary and the perturbation theory that can be derived is equivalent to the…

High Energy Physics - Theory · Physics 2015-02-03 Johnny Espin

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment…

Numerical Analysis · Mathematics 2023-06-21 Di Qi , Jian-Guo Liu

The nonlinear saturation of the tearing mode is revisited in slab geometry by taking into account higher-order harmonics in the outer solution. The general formalism for tackling this problem in the case of a vanishing current gradient at…

Plasma Physics · Physics 2009-11-13 N. Arcis , N. F. Loureiro , F. Militello

Spectral methods of moments provide a powerful tool for learning the parameters of latent variable models. Despite their theoretical appeal, the applicability of these methods to real data is still limited due to a lack of robustness to…

Machine Learning · Statistics 2018-10-18 Matteo Ruffini , Guillaume Rabusseau , Borja Balle

Choice modeling is at the core of understanding how changes to the competitive landscape affect consumer choices and reshape market equilibria. In this paper, we propose a fundamental characterization of choice functions that encompasses a…

Econometrics · Economics 2024-02-21 Amandeep Singh , Ye Liu , Hema Yoganarasimhan

In this paper, we propose a high-order extension of the multiscale method introduced by the authors in [SIAM J. Numer. Anal., 63(4) (2025), pp. 1617--1641] for heterogeneous Stokes problems, while also providing several other improvements,…

Numerical Analysis · Mathematics 2025-12-01 Moritz Hauck , Alexei Lozinski

This paper is devoted to the study of metric subregularity and strong subregularity of any positive order $q$ for set-valued mappings in finite and infinite dimensions. While these notions have been studied and applied earlier for $q=1$…

Optimization and Control · Mathematics 2015-07-20 Boris Mordukhovich , Wei Ouyang

In this paper, we show that a suitably chosen covariance function of a continuous time, second order stationary stochastic process can be viewed as a symmetric higher order kernel. This leads to the construction of a higher order kernel by…

Statistics Theory · Mathematics 2020-01-22 Soumya Das , Subhajit Dutta , Radhenduhska Srivastava

This paper describes the use of a quadratic manifold for the model order reduction of structural dynamics problems featuring geometric nonlinearities. The manifold is tangent to a subspace spanned by the most relevant vibration modes, and…

Computational Engineering, Finance, and Science · Computer Science 2017-05-22 Shobhit Jain , Paolo Tiso , Daniel J. Rixen , Johannes B. Rutzmoser

The industrial application motivating this work is the fatigue computation of aircraft engines' high-pressure turbine blades. The material model involves nonlinear elastoviscoplastic behavior laws, for which the parameters depend on the…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Nissrine Akkari

Multi-material design optimization problems can, after discretization, be solved by the iterative solution of simpler sub-problems which approximate the original problem at an expansion point to first order. In particular, models…

Numerical Analysis · Mathematics 2026-04-01 Peter Gangl , Nico Nees , Michael Stingl

We construct a class of real-valued nonnegative binary functions on a set of jointly distributed random variables, which satisfy the triangle inequality and vanish at identical arguments (pseudo-quasi-metrics). These functions are useful in…

Probability · Mathematics 2016-02-12 Ehtibar N. Dzhafarov , Janne V. Kujala

We study the finite element approximation of linear second-order elliptic partial differential equations in nondivergence form with highly heterogeneous diffusion and drift coefficients. A generalized Cordes condition is imposed to…

Numerical Analysis · Mathematics 2026-04-17 Moritz Hauck , Roland Maier , Timo Sprekeler

In this paper, we show that higher-order optimality conditions can be obtain for arbitrary nonsmooth function. We introduce a new higher-order directional derivative and higher-order subdifferential of Hadamard type of a given proper…

Optimization and Control · Mathematics 2013-11-12 Vsevolod Ivanov Ivanov

A novel approximation method in studying the perihelion precession and planetary orbits in general relativity is to use geodesic deviation equations of first and high-orders, proposed by Kerner et.al. Using higher-order geodesic deviation…

General Relativity and Quantum Cosmology · Physics 2019-07-16 Mohaddese Heydari-Fard , Malihe Heydari-Fard , Hamid Reza Sepangi

In this paper, we consider the nonparametric random regression model $Y=f_1(X_1)+f_2(X_2)+\epsilon$ and address the problem of estimating the function $f_1$. The term $f_2(X_2)$ is regarded as a nuisance term which can be considerably more…

Statistics Theory · Mathematics 2015-02-03 Martin Wahl
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