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The combination of the Reduced Basis and the Empirical Interpolation Method (EIM) approaches have produced outstanding results in many disciplines. In particular, in gravitational wave (GW) science these results range from building…

Numerical Analysis · Mathematics 2021-07-07 Manuel Tiglio , Aarón Villanueva

We consider and discretize a mixed formulation for linear elasticity with weakly imposed symmetry in two and three dimensions. Whereas existing methods mainly deal with simplicial or polygonal meshes, we take advantage of isogeometric…

Numerical Analysis · Mathematics 2022-10-20 Jeremias Arf

We present a novel way of accelerating hybrid surrogate methods for the calculation of failure probabilities. The main idea is to use mesh refinement in order to obtain improved local surrogates of low computation cost to simulate on. These…

Numerical Analysis · Mathematics 2015-09-23 Jing Li , Panos Stinis

This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are available. A tried and tested technique is to build surrogates of the objective and the…

Optimization and Control · Mathematics 2022-08-18 Charles Audet , Sébastien Le Digabel , Renaud Saltet

The advent of multi-material additive manufacturing and automated composite manufacturing has enabled the design of structures featuring complex curvilinear anisotropy. To take advantage of the new design space, efficient computational…

Applied Physics · Physics 2020-10-05 Kenta Suzuki , Sean E. Phenisee , Marco Salviato

Recent advances in the field of machine learning open a new era in high performance computing. Applications of machine learning algorithms for the development of accurate and cost-efficient surrogates of complex problems have already…

Numerical Analysis · Mathematics 2022-08-26 Stefanos Nikolopoulos , Ioannis Kalogeris , Vissarion Papadopoulos , George Stavroulakis

Surrogate models are used for global approximation of responses generated by expensive computer experiments like CFD applications. In this paper, we make use of structural similarities which are shared by a class of related problems. We…

Numerical Analysis · Mathematics 2012-06-20 Benjamin Rosenbaum , Volker Schulz

We compare convergence of isogeometric analysis (IGA), a spline modification of finite element method (FEM), with FEM in the context of our real space code for ab-initio electronic structure calculations of non-periodic systems. The…

Computational Physics · Physics 2021-01-07 Robert Cimrman , Matyáš Novák , Radek Kolman , Miroslav Tůma , Jiří Vackář

AI-driven surrogate modeling has become an increasingly effective alternative to physics-based simulations for 3D design, analysis, and manufacturing. These models leverage data-driven methods to predict physical quantities traditionally…

Machine Learning · Computer Science 2025-05-06 Yu-hsuan Chen , Jing Bi , Cyril Ngo Ngoc , Victor Oancea , Jonathan Cagan , Levent Burak Kara

Multi-material problems often exhibit complex geometries along with physical responses presenting large spatial gradients or discontinuities. In these cases, providing high-quality body-fitted finite element analysis meshes and obtaining…

Numerical Analysis · Mathematics 2022-02-14 L. Noel , M. Schmidt , K. Doble , J. A. Evans , K. Maute

Gaussian processes (GPs) serve as flexible surrogates for complex surfaces, but buckle under the cubic cost of matrix decompositions with big training data sizes. Geospatial and machine learning communities suggest pseudo-inputs, or…

Methodology · Statistics 2021-02-05 D. Austin Cole , Ryan Christianson , Robert B. Gramacy

In this paper, we focus on solving a sequence of linear systems with an identical (or similar) coefficient matrix. For this type of problems, we investigate the subspace correction and deflation methods, which use an auxiliary matrix…

Numerical Analysis · Mathematics 2022-03-17 Takeshi Iwashita , Kota Ikehara , Takeshi Fukaya , Takeshi Mifune

The present paper proposes a Bayesian framework for inverse problems that seamlessly integrates optimization and inversion to enable rapid surrogate modeling, accurate parameter inference, and rigorous uncertainty quantification. Bayesian…

Computational Engineering, Finance, and Science · Computer Science 2026-02-05 Mihaela Chiappetta , Massimo Carraturo , Alexander Raßloff , Markus Kästner , Ferdinando Auricchio

This work presents an efficient quadrature rule for shell analysis fully integrated in CAD by means of Isogeometric Analysis (IGA). General CAD-models may consist of trimmed parts such as holes, intersections, cut-offs etc. Therefore, IGA…

Computational Engineering, Finance, and Science · Computer Science 2023-08-09 Michael Loibl , Leonardo Leonetti , Alessandro Reali , Josef Kiendl

Inverse problems are prevalent in both scientific research and engineering applications. In the context of Bayesian inverse problems, sampling from the posterior distribution can be particularly challenging when the forward models are…

Computation · Statistics 2026-02-17 Zhihang Xu , Xiaoyu Zhu , Daoji Li , Qifeng Liao

This paper presents a novel learning-based approach to construct a surrogate problem that approximates a given parametric nonconvex optimization problem. The surrogate function is designed to be the minimum of a finite set of functions,…

Optimization and Control · Mathematics 2026-04-08 Renzi Wang , Panagiotis Patrinos , Alberto Bemporad

The study of quantum three-body problems has been centered on low-energy states that rely on accurate numerical approximation. Recently, isogeometric analysis (IGA) has been adopted to solve the problem as an alternative but more robust…

Numerical Analysis · Mathematics 2023-01-25 Danyang Li , Quanling Deng

A Skeleton-stabilized IsoGeometric Analysis (SIGA) technique is proposed for incompressible viscous flow problems with moderate Reynolds number. The proposed method allows utilizing identical finite dimensional spaces (with arbitrary…

In this paper we discuss the numerical solution on a simple 2D domain of the Helmoltz equation with mixed boundary conditions. The so called radiation problem depends on the wavenumber constant parameter k and it is inspired here by medical…

A new algorithm is developed to tackle the issue of sampling non-Gaussian model parameter posterior probability distributions that arise from solutions to Bayesian inverse problems. The algorithm aims to mitigate some of the hurdles faced…

Machine Learning · Statistics 2019-11-19 Leen Alawieh , Jonathan Goodman , John B. Bell
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