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A structure preserving proper orthogonal decomposition reduce-order modeling approach has been developed in [Gong et al. 2017] for the Hamiltonian system, which uses the traditional framework of Galerkin projection-based model reduction but…

Numerical Analysis · Mathematics 2021-03-03 Zhu Wang

In this paper, we build up a framework for sparse interpolation. We first investigate the theoretical limit of the number of unisolvent points for sparse interpolation under a general setting and try to answer some basic questions of this…

Numerical Analysis · Mathematics 2013-08-30 Zhiqiang Xu , Tao Zhou

Stochastic interpolants unify flows and diffusions, popular generative modeling frameworks. A primary hyperparameter in these methods is the interpolation schedule that determines how to bridge a standard Gaussian base measure to an…

Machine Learning · Statistics 2026-02-04 Gabriel Damsholt , Jes Frellsen , Susanne Ditlevsen

Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this structure, we can use just a few spatially localized sensor…

Statistical Mechanics · Physics 2025-09-16 Andrei A. Klishin , J. Nathan Kutz , Krithika Manohar

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

A useful sampling-reconstruction model should be stable with respect to different kind of small perturbations, regardless whether they result from jitter, measurement errors, or simply from a small change in the model assumptions. In this…

General Mathematics · Mathematics 2007-05-31 E. costa-Reyes , A. Aldroubi , I. Krishtal

Determining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 Damián G. Hernández , Inés Samengo

This paper presents new results concerning the observer design for wide classes of nonlinear systems with both sampled and delayed measurements. By using a small gain approach we provide sufficient conditions, which involve both the delay…

Optimization and Control · Mathematics 2012-07-05 Tarek Ahmed-Ali , Iasson Karafyllis , Francoise Lamnabhi-Lagarrigue

The recovery of sparsest overcomplete representation has recently attracted intensive research activities owe to its important potential in the many applied fields such as signal processing, medical imaging, communication, and so on. This…

Information Theory · Computer Science 2011-09-29 Lianlin Li

Detecting weak, systematic distribution shifts and quantitatively modeling individual, heterogeneous responses to policies or incentives have found increasing empirical applications in social and economic sciences. Given two probability…

Statistics Theory · Mathematics 2024-03-29 YoonHaeng Hur , Tengyuan Liang

Interpolation inequalities play an essential role in Analysis with fundamental consequences in Mathematical Physics, Nonlinear Partial Differential Equations (PDEs), Markov Processes, etc., and have a wide range of applications in various…

Analysis of PDEs · Mathematics 2021-10-19 Jean Dolbeault

Optimal convergence rates of adaptive finite element methods are well understood in terms of the axioms of adaptivity. One key ingredient is the discrete reliability of a residual-based a posteriori error estimator, which controls the error…

Numerical Analysis · Mathematics 2019-11-06 Carsten Carstensen , Sophie Puttkammer

We present a nonlinear interpolation technique for parametric fields that exploits optimal transportation of coherent structures of the solution to achieve accurate performance. The approach generalizes the nonlinear interpolation procedure…

Numerical Analysis · Mathematics 2023-10-09 Simona Cucchiara , Angelo Iollo , Tommaso Taddei , Haysam Telib

The problem of sampling a discrete-time sequence of spatially bandlimited fields with a bounded dynamic range, in a distributed, communication-constrained, processing environment is addressed. A central unit, having access to the data…

Information Theory · Computer Science 2016-11-18 Animesh Kumar , Prakash Ishwar , Kannan Ramchandran

This paper investigates the stability of the least squares approximation $P_m^n$ within the univariate polynomial space of degree $m$, denoted by ${\mathbb P}_m$. The approximation $P_m^n$ entails identifying a polynomial in ${\mathbb P}_m$…

Numerical Analysis · Mathematics 2026-02-17 Zhiqiang Xu , Xinyue Zhang

Many high dimensional integrals can be reduced to the problem of finding the relative measures of two sets. Often one set will be exponentially larger than the other, making it difficult to compare the sizes. A standard method of dealing…

Probability · Mathematics 2011-12-19 Mark Huber , Sarah Schott

A quasi two-dimensional colloidal suspension is studied under the influence of immobilisation (pinning) of a random fraction of its particles. We introduce a novel experimental method to perform random pinning and, with the support of…

This paper is addressed to a stabilization problem of a system coupled by a wave and a Euler-Bernoulli plate equation. Only one equation is supposed to be damped. Under some assumption about the damping and the coupling terms, it is shown…

Optimization and Control · Mathematics 2018-01-03 Xiaoyu Fu , Qi Lu

This paper addresses the synthesis of interval observers for partially unknown nonlinear systems subject to bounded noise, aiming to simultaneously estimate system states and learn a model of the unknown dynamics. Our approach leverages…

Systems and Control · Electrical Eng. & Systems 2025-04-15 Mohammad Khajenejad , Zeyuan Jin

Environmental research increasingly uses high-dimensional remote sensing and numerical model output to help fill space-time gaps between traditional observations. Such output is often a noisy proxy for the process of interest. Thus one…

Methodology · Statistics 2012-04-30 Christopher J. Paciorek