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The focus of this work is on the development of an error-driven isogeometric framework, capable of automatically performing an adaptive simulation in the context of second- and fourth-order, elliptic partial differential equations defined…

Numerical Analysis · Mathematics 2020-04-22 Luca Coradello , Pablo Antolin , Rafael Vázquez , Annalisa Buffa

In this paper, we propose a stochastic geometric iterative method to approximate the high-resolution 3D models by finite Loop subdivision surfaces. Given an input mesh as the fitting target, the initial control mesh is generated using the…

Graphics · Computer Science 2021-07-30 Chenkai Xu , Yaqi He , Hui Hu , Hongwei Lin

We consider the problem of recovering elements of a low-dimensional model from linear measurements. From signal and image processing to inverse problems in data science, this question has been at the center of many applications. Lately,…

Signal Processing · Electrical Eng. & Systems 2025-05-15 Yann Traonmilin , Jean François Aujol , Antoine Guennec

In this work, we further develop multigoal-oriented a posteriori error estimation with two objectives in mind. First, we formulate goal-oriented mesh adaptivity for multiple functionals of interest for nonlinear problems in which both the…

Numerical Analysis · Mathematics 2018-04-05 B. Endtmayer , U. Langer , T. Wick

This paper is concerned with the nonconforming finite element discretization of geometric partial differential equations. In specific, we construct a surface Crouzeix-Raviart element on the linear approximated surface, analogous to a flat…

Numerical Analysis · Mathematics 2022-08-12 Hailong Guo

In this paper, we study a modified residual-based a posteriori error estimator for the nonconforming linear finite element approximation to the interface problem. The reliability of the estimator is analyzed by a new and direct approach…

Numerical Analysis · Mathematics 2016-11-23 Zhiqiang Cai , Cuiyu He , Shun Zhang

We present an a posteriori error analysis for the mixed virtual element method (mixed VEM) applied to second order elliptic equations in divergence form with mixed boundary conditions. The resulting error estimator is of residual-type. It…

Numerical Analysis · Mathematics 2019-04-24 Andrea Cangiani , Mauricio Munar

Elliptic partial differential equations are important both from application and analysis points of views. In this paper we apply the Closest Point Method to solving elliptic equations on general curved surfaces. Based on the closest point…

Numerical Analysis · Mathematics 2014-10-28 Yujia Chen , Colin B. Macdonald

The velocity, coupling term in the flow and transport problems, is important in the accurate numerical simulation or in the posteriori error analysis for adaptive mesh refinement. We consider Enhanced Velocity Mixed Finite Element Method…

Numerical Analysis · Mathematics 2024-12-20 Yerlan Amanbek , Gurpreet Singh , Mary F. Wheeler

In this paper a new hp-adaptive strategy for elliptic problems based on refinement history is proposed, which chooses h-, p- or hp-refinement on individual elements according to a posteriori error estimate, as well as smoothness estimate of…

Numerical Analysis · Computer Science 2017-01-25 Hui Liu , Tao Cui , Wei Leng , Linbo Zhang

In this paper we develop a $C^0$-conforming virtual element method (VEM) for a class of second-order quasilinear elliptic PDEs in two dimensions. We present a posteriori error analysis for this problem and derive a residual based error…

Numerical Analysis · Mathematics 2024-09-27 Scott Congreve , Alice Hodson

Two asymptotically exact a posteriori error estimates are proposed for eigenvalues by the nonconforming Crouzeix--Raviart and enriched Crouzeix-- Raviart elements. The main challenge in the design of such error estimators comes from the…

Numerical Analysis · Mathematics 2019-11-26 Jun Hu , Limin Ma

We propose a novel optimization-based paradigm for 3D human model fitting on images and scans. In contrast to existing approaches that directly regress the parameters of a low-dimensional statistical body model (e.g. SMPL) from input…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Enric Corona , Gerard Pons-Moll , Guillem Alenyà , Francesc Moreno-Noguer

Elliptic reconstruction property, originally introduced by Makridakis and Nochetto for linear parabolic problems, is a well-known tool to derive optimal a posteriori error estimates. No such results are known for nonlinear and nonsmooth…

Numerical Analysis · Mathematics 2024-05-29 Harbir Antil , Rohit Khandelwal

The solution of the elliptic partial differential equation has interface singularity at the points which are either the intersections of interfaces or the intersections of interfaces with the boundary of the domain. The singularities that…

Numerical Analysis · Mathematics 2020-03-05 N. Kishore Kumar , Pankaj Biswas , B. Seshadri Reddy

The matched interface and boundary (MIB) method has a proven ability for delivering the second order accuracy in handling elliptic interface problems with arbitrarily complex interface geometries. However, its collocation formulation…

Numerical Analysis · Mathematics 2015-09-04 Yin Cao , Bao Wang , Kelin Xia , Guowi Wei

We introduce generalised finite difference methods for solving fully nonlinear elliptic partial differential equations. Methods are based on piecewise Cartesian meshes augmented by additional points along the boundary. This allows for…

Numerical Analysis · Mathematics 2017-06-26 Brittany D. Froese , Tiago Salvador

We present the Multilevel Bregman Proximal Gradient Descent (ML BPGD) method, a novel multilevel optimization framework tailored to constrained convex problems with relative Lipschitz smoothness. Our approach extends the classical…

Optimization and Control · Mathematics 2026-05-06 Yara Elshiaty , Stefania Petra

Adaptive multilevel finite element methods are developed and analyzed for certain elliptic systems arising in geometric analysis and general relativity. This class of nonlinear elliptic systems of tensor equations on manifolds is first…

Numerical Analysis · Mathematics 2010-01-12 Michael Holst

Many statistical $M$-estimators are based on convex optimization problems formed by the combination of a data-dependent loss function with a norm-based regularizer. We analyze the convergence rates of projected gradient and composite…

Machine Learning · Statistics 2012-07-26 Alekh Agarwal , Sahand N. Negahban , Martin J. Wainwright