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The present paper deals with the data-driven design of regularizers in the form of artificial neural networks, for solving certain inverse problems formulated as optimal control problems. These regularizers aim at improving accuracy,…

Optimization and Control · Mathematics 2023-03-06 Sebastien Court

Consider the problem of inverse scattering of time-harmonic point sources from an infinite, penetrable rough interface with bounded obstacles buried in the lower half-space, where the interface is assumed to be a local perturbation of a…

Analysis of PDEs · Mathematics 2020-09-02 Jianliang Li , Jiaqing Yang , Bo Zhang

Quadratic constraints (QCs) are widely used to characterize nonlinearities and uncertainties, but generic analytical characterizations can be conservative on bounded domains. This paper develops a framework for constructing verified…

Machine Learning · Computer Science 2026-05-21 Elias Khalife , Mazen Farhood , Pierre-Loic Garoche

Subcritical transition to turbulence in spatially developing boundary layer flows can be triggered efficiently by finite amplitude perturbations. In this work, we employ adjoint-based optimization to identify optimal initial perturbations…

Fluid Dynamics · Physics 2020-12-16 Chris Vavaliaris , Miguel Beneitez , Dan S. Henningson

Source-tract decomposition (or glottal flow estimation) is one of the basic problems of speech processing. For this, several techniques have been proposed in the literature. However studies comparing different approaches are almost…

Sound · Computer Science 2020-01-06 Thomas Drugman , Baris Bozkurt , Thierry Dutoit

The interaction between shear driven turbulence and stratification is a key process in a wide array of geophysical flows with spatio-temporal scales that span many orders of magnitude. A quick numerical model prediction based on external…

Fluid Dynamics · Physics 2021-08-18 M. A. Ahmed , H. J. Bae , A. F. Thompson , B. J. McKeon

This work proposes a new way for handling obstacles to asymptotic integrability in perturbed nonlinear PDEs within the method of Normal Forms - NF - for the case of multi-wave solutions. Instead of including the whole obstacle in the NF,…

Exactly Solvable and Integrable Systems · Physics 2009-11-11 Alex Veksler , Yair Zarmi

In this thesis I discuss analytical approaches to disordered systems using field theory. Disordered systems are characterized by a random energy landscape due to heterogeneities, which remains fixed on the time scales of the phenomena…

Disordered Systems and Neural Networks · Physics 2013-12-30 Alexander Dobrinevski

A systematic study of small, time-dependent, perturbations to geometric wave-equation domains is hardly existent. Acoustic enclosures are typical examples featuring locally reacting surfaces that respond to a pressure gradient or a pressure…

Mathematical Physics · Physics 2018-01-03 David T. Heider , J. Leo van Hemmen

This work applies resolvent analysis to incompressible flow through a rectangular duct, in order to identify dominant linear energy-amplification mechanisms present in such flows. In particular, we formulate the resolvent operator from…

Fluid Dynamics · Physics 2022-05-30 Barbara Lopez-Doriga , Scott T. M. Dawson , Ricardo Vinuesa

Irregular terrain has a pronounced effect on the propagation of seismic and acoustic wavefields but is not straightforwardly reconciled with structured finite-difference (FD) methods used to model such phenomena. Methods currently detailed…

Numerical Analysis · Mathematics 2023-09-08 Edward Caunt , Rhodri Nelson , Fabio Luporini , Gerard Gorman

We consider the inverse obstacle scattering problem of determining both the shape and the "equivalent impedance" from far field measurements at a fixed frequency. In this work, the surface impedance is represented by a second order surface…

Numerical Analysis · Mathematics 2013-07-24 Laurent Bourgeois , Nicolas Chaulet , Houssem Haddar

Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the inherently ill-posed nature of the inversion problem, directly estimating impedance from post-stack…

Machine Learning · Computer Science 2025-06-17 Jie Chen , Hongling Chen , Jinghuai Gao , Chuangji Meng , Tao Yang , XinXin Liang

The Error-in-Variables model of system identification/control involves nontrivial input and measurement corruption of observed data, resulting in generically nonconvex optimization problems. This paper performs full-state-feedback…

Optimization and Control · Mathematics 2024-05-21 Jared Miller , Tianyu Dai , Mario Sznaier

The problem of disturbed flow in the laminar boundary layer is investigated when a heating element is located on the surface of the body. The flow is supposed to be laminar one. It is shown that the problem may be solved in terms of free…

Fluid Dynamics · Physics 2011-10-13 M. V. Koroteev , I. I. Lipatov

This work focuses on the mathematical modeling of wave dynamics in a stratified medium. Non-local absorbing boundary conditions are considered based on the two following assumptions: (i) a linear theory can be applied at large distances…

Fluid Dynamics · Physics 2010-08-25 Vitaly V. Bulatov , Yuriy V. Vladimirov

When a language model is fed a wrong answer, what happens inside the network? Current understanding treats truthfulness as a static property of individual-layer representations-a direction to be probed, a feature to be extracted. Less is…

Computation and Language · Computer Science 2026-03-17 Javier Marín

Resilience has emerged as a crucial concept for evaluating structural performance under disasters because of its ability to extend beyond traditional risk assessments, accounting for a system's ability to minimize disruptions and maintain…

Applications · Statistics 2024-04-23 Taeyong Kim , Sang-ri Yi

This paper is devoted to a novel quantitative imaging scheme of identifying impenetrable obstacles in time-harmonic acoustic scattering from the associated far-field data. The proposed method consists of two phases. In the first phase, we…

Numerical Analysis · Mathematics 2023-07-05 Youzi He , Hongyu Liu , Xianchao Wang

Dealing with non-stationarity in environments (e.g., in the transition dynamics) and objectives (e.g., in the reward functions) is a challenging problem that is crucial in real-world applications of reinforcement learning (RL). While most…

Machine Learning · Computer Science 2022-10-19 Fan Feng , Biwei Huang , Kun Zhang , Sara Magliacane