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A test oracle serves as a criterion or mechanism to assess the correspondence between software output and the anticipated behavior for a given input set. In automated testing, black-box techniques, known for their non-intrusive nature in…

Software Engineering · Computer Science 2023-10-11 Boxi Yu , Qiuyang Mang , Qingshuo Guo , Pinjia He

This paper describes a generalization of Clark's completion that is applicable to logic programs containing arithmetic operations and produces syntactically simple, natural looking formulas. If a set of first-order axioms is equivalent to…

Logic in Computer Science · Computer Science 2023-05-25 Vladimir Lifschitz

The present paper reports on the recent activity of the data analysis software development for total-reflection high-energy positron diffraction (TRHEPD), a novel experimental technique for surface structure determination. Experiments using…

Materials Science · Physics 2020-07-14 Kazuyuki Tanaka , Takeo Hoshi , Izumi Mochizuki , Takashi Hanada , Ayahiko Ichimiya , Toshio Hyodo

To fully leverage the power of image simulation to corroborate and explain patterns and structures in atomic resolution microscopy (e.g., electron and scanning probe), an initial correspondence between the simulation and experimental image…

Convexity, though extremely important in mathematical programming, has not drawn enough attention in the field of dynamic programming. This paper gives conditions for verifying convexity of the cost-to-go functions, and introduces an…

Optimization and Control · Mathematics 2011-11-14 Sheng Yu , Enrique Campos-Nanez

Inverse scattering problems of the reconstructions of physical properties of a medium from boundary measurements are substantially challenging ones. This work aims to verify the performance on experimental data of a newly developed…

This paper is concerned with the convergence of a series associated with a certain version of the convexification method. That version has been recently developed by the research group of the first author for solving coefficient inverse…

Numerical Analysis · Mathematics 2023-03-13 Michael V. Klibanov , Dinh-Liem Nguyen

We propose to solve inverse problems involving the temporal evolution of physics systems by leveraging recent advances from diffusion models. Our method moves the system's current state backward in time step by step by combining an…

Machine Learning · Computer Science 2023-12-06 Benjamin J. Holzschuh , Simona Vegetti , Nils Thuerey

A novel trust region method for solving linearly constrained nonlinear programs is presented. The proposed technique is amenable to a distributed implementation, as its salient ingredient is an alternating projected gradient sweep in place…

Optimization and Control · Mathematics 2015-08-04 Jean-Hubert Hours , Colin N. Jones

The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this setting is backpropagation through the solution of an…

Machine Learning · Computer Science 2024-01-01 James Kotary , Jacob Christopher , My H Dinh , Ferdinando Fioretto

We consider the problem of reconstructing the shape of an impenetrable sound-soft obstacle from scattering measurements. The input data is assumed to be the far-field pattern generated when a plane wave impinges on an unknown obstacle from…

Numerical Analysis · Mathematics 2015-05-28 Carlos Borges , Leslie Greengard

This paper is concerned with the inverse scattering problem which aims to determine the spatially distributed dielectric constant coefficient of the 2D Helmholtz equation from multifrequency backscatter data associated with a single…

Numerical Analysis · Mathematics 2020-02-25 Trung Truong , Dinh-Liem Nguyen , Michael Klibanov

The high energy physics unfolding problem is an important statistical inverse problem in data analysis at the Large Hadron Collider (LHC) at CERN. The goal of unfolding is to make nonparametric inferences about a particle spectrum from…

Applications · Statistics 2017-06-09 Mikael Kuusela , Philip B. Stark

Reproducibility of results is a cornerstone of the scientific method. Scientific computing encounters two challenges when aiming for this goal. Firstly, reproducibility should not depend on details of the runtime environment, such as the…

General Relativity and Quantum Cosmology · Physics 2023-12-12 Yufeng Luo , Qian Zhang , Roland Haas , Zachariah B. Etienne , Gabrielle Allen

These lecture notes highlight the mathematical and computational structure relating to the formulation of, and development of algorithms for, the Bayesian approach to inverse problems in differential equations. This approach is fundamental…

Probability · Mathematics 2015-07-03 Masoumeh Dashti , Andrew M. Stuart

Many quantum systems are being investigated in the hope of building a large-scale quantum computer. All of these systems suffer from decoherence, resulting in errors during the execution of quantum gates. Quantum error correction enables…

Quantum Physics · Physics 2012-10-25 Austin G. Fowler , Adam C. Whiteside , Angus L. McInnes , Alimohammad Rabbani

Reconstructing unknown external source functions is an important perception capability for a large range of robotics domains including manipulation, aerial, and underwater robotics. In this work, we propose a Physics-Informed Neural Network…

Robotics · Computer Science 2024-11-05 Youngsun Wi , Jayjun Lee , Miquel Oller , Nima Fazeli

The motivation of this work is an inverse problem for the acoustic wave equation, where an array of sensors probes an unknown medium with pulses and measures the scattered waves. The goal of the inversion is to determine from these…

Numerical Analysis · Mathematics 2018-06-18 Liliana Borcea , Vladimir Druskin , Alexander V. Mamonov , Mikhail Zaslavsky

This paper describes a new MATLAB software package of iterative regularization methods and test problems for large-scale linear inverse problems. The software package, called IR Tools, serves two related purposes: we provide implementations…

Numerical Analysis · Mathematics 2018-07-03 Silvia Gazzola , Per Christian Hansen , James G. Nagy

In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately estimating optical flow under conditions of large nonlinear motion patterns remains an open…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Chanuka Algama , Kasun Amarasinghe