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A variety of shooting methods for computing fully discrete time-periodic solutions of partial differential equations, including Newton-Krylov and optimization-based methods, are discussed and used to determine the periodic, compressible,…

Optimization and Control · Mathematics 2016-08-16 Matthew J. Zahr , Per-Olof Persson , Jon Wilkening

This paper considers a general data-fitting problem over a networked system, in which many computing nodes are connected by an undirected graph. This kind of problem can find many real-world applications and has been studied extensively in…

Machine Learning · Computer Science 2017-04-14 Ying Zhang

Image segmentation is an inherently ill-posed problem and thus requires regularization in order to limit the search space to reasonable solutions. A majority of segmentation methods integrates these regularization terms in one way or the…

Numerical Analysis · Mathematics 2018-10-31 Uri Nahum , Philippe C. Cattin

We propose a neural network-based meta-learning method to efficiently solve partial differential equation (PDE) problems. The proposed method is designed to meta-learn how to solve a wide variety of PDE problems, and uses the knowledge for…

Machine Learning · Statistics 2023-10-23 Tomoharu Iwata , Yusuke Tanaka , Naonori Ueda

A finite element method for elliptic problems with discontinuous coefficients is presented. The discontinuity is assumed to take place along a closed smooth curve. The proposed method allows to deal with meshes that are not adapted to the…

Numerical Analysis · Mathematics 2007-07-12 Gunther H. Peichl , Rachid Touzani

We investigate an optimization problem governed by an elliptic partial differential equation with uncertain parameters. We introduce a robust optimization framework that accounts for uncertain model parameters. The resulting non-linear…

Optimization and Control · Mathematics 2019-09-24 Alessandro Alla , Michael Hinze , Philip Kolvenbach , Oliver Lass , Stefan Ulbrich

Artificial Neuronal Networks are models widely used for many scientific tasks. One of the well-known field of application is the approximation of high-dimensional problems via Deep Learning. In the present paper we investigate the Deep…

Numerical Analysis · Mathematics 2021-10-06 F. Calabrò , S. Cuomo , F. Giampaolo , S. Izzo , C. Nitsch , F. Piccialli , C. Trombetti

Network models are used as efficient representation of materials with complex, interconnected locally one-dimensional structures. They typically accurately capture the mechanical properties of a material, while substantially reducing…

Numerical Analysis · Mathematics 2025-12-16 Morgan Görtz , Moritz Hauck , Axel Målqvist , Andreas Rupp , Lucia Swoboda

Deformable image registration is a fundamental problem in the field of medical image analysis. During the last years, we have witnessed the advent of deep learning-based image registration methods which achieve state-of-the-art performance,…

Image and Video Processing · Electrical Eng. & Systems 2020-02-03 Lucas Mansilla , Diego H. Milone , Enzo Ferrante

Hypergraph matching has recently become a popular approach for solving correspondence problems in computer vision as it allows to integrate higher-order geometric information. Hypergraph matching can be formulated as a third-order…

Computer Vision and Pattern Recognition · Computer Science 2016-11-17 Quynh Nguyen , Francesco Tudisco , Antoine Gautier , Matthias Hein

Aligning partially overlapping point sets where there is no prior information about the value of the transformation is a challenging problem in computer vision. To achieve this goal, we first reduce the objective of the robust point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Wei Lian , WangMeng Zuo , Lei Zhang

The present work proposes a solution to the challenging problem of registering two partial point sets of the same object with very limited overlap. We leverage the fact that most objects found in man-made environments contain a plane of…

Computational Geometry · Computer Science 2020-02-20 Lan Hu , Haomin Shi , Laurent Kneip

Learning non-rigid registration in an end-to-end manner is challenging due to the inherent high degrees of freedom and the lack of labeled training data. In this paper, we resolve these two challenges simultaneously. First, we propose to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Wanquan Feng , Juyong Zhang , Hongrui Cai , Haofei Xu , Junhui Hou , Hujun Bao

In this paper, we propose a learning-based image fragment pair-searching and -matching approach to solve the challenging restoration problem. Existing works use rule-based methods to match similar contour shapes or textures, which are…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Rixin Zhou , Ding Xia , Yi Zhang , Honglin Pang , Xi Yang , Chuntao Li

We establish that nonconvex definable parametric optimization problems with possibly nonsmooth objectives, inequality constraints, conic constraint systems, and non-unique primal and dual solutions admit an adjoint state formula under a…

Optimization and Control · Mathematics 2026-04-23 Jérôme Bolte , Edouard Pauwels , Cheik Traoré

In this paper, we consider the problem of accelerating the numerical simulation of time dependent problems by time domain decomposition. The available algorithms enabling such decompositions present severe efficiency limitations and are an…

Numerical Analysis · Mathematics 2020-03-27 Y. Maday , O. Mula

The free-form deformation model can represent a wide range of non-rigid deformations by manipulating a control point lattice over the image. However, due to a large number of parameters, it is challenging to fit the free-form deformation…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Takumi Nakane , Haoran Xie , Chao Zhang

The convergence of an adaptive mixed finite element method for general second order linear elliptic problems defined on simply connected bounded polygonal domains is analyzed in this paper. The main difficulties in the analysis are posed by…

Numerical Analysis · Mathematics 2014-02-14 Asha K. Dond , Neela Nataraj , Amiya K. Pani

In this work, we develop a framework for shape analysis using inconsistent surface mapping. Traditional landmark-based geometric morphometrics methods suffer from the limited degrees of freedom, while most of the more advanced non-rigid…

Computational Geometry · Computer Science 2020-10-30 Gary P. T. Choi , Di Qiu , Lok Ming Lui

A class of evolution quasistatic systems which leads, after a suitable time discretization, to recursive nonlinear programs, is considered and optimal control or identification problems governed by such systems are investigated. The…

Optimization and Control · Mathematics 2014-11-19 L. Adam , J. V. Outrata , T. Roubicek