English
Related papers

Related papers: High-Order Mesh r-Adaptivity with Tangential Relax…

200 papers

Reduced-order models (ROMs) are essential for rapid simulation of complex biomechanical systems and for bridging the gap between high fidelity models and clinical application. However, ROMs for tissue growth and remodeling (G&R) remain…

Computational Engineering, Finance, and Science · Computer Science 2026-04-16 Joel Laudo , Adrian Buganza Tepole

This is a study of certain finite element methods designed for convection-dominated, time-dependent partial differential equations. Specifically, we analyze high order space-time tensor product finite element discretizations, used in a…

Numerical Analysis · Mathematics 2013-10-30 Randolph E. Bank , Maximilian S. Metti

We present a novel adaptive optimization algorithm for large-scale machine learning problems. Equipped with a low-cost estimate of local curvature and Lipschitz smoothness, our method dynamically adapts the search direction and step-size.…

Machine Learning · Computer Science 2021-09-14 Majid Jahani , Sergey Rusakov , Zheng Shi , Peter Richtárik , Michael W. Mahoney , Martin Takáč

A second-order face-centred finite volume strategy on general meshes is proposed. The method uses a mixed formulation in which a constant approximation of the unknown is computed on the faces of the mesh. Such information is then used to…

Numerical Analysis · Mathematics 2020-12-01 Matteo Giacomini , Ruben Sevilla

High-order implicit shock tracking (fitting) is a class of high-order, optimization-based numerical methods to approximate solutions of conservation laws with non-smooth features by aligning elements of the computational mesh with…

Numerical Analysis · Mathematics 2024-01-30 Charles J. Naudet , Matthew J. Zahr

Topology optimization is concerned with the identification of optimal shapes of deformable bodies with respect to given target functionals. The focus of this paper is on a topology optimization problem for a time-evolving elastoplastic…

Analysis of PDEs · Mathematics 2021-06-21 Stefano Almi , Ulisse Stefanelli

A novel fifth-order compact gas-kinetic scheme is developed for high-resolution simulation of compressible flows on structured meshes. Its accuracy relies on a new multidimensional fifth-order compact reconstruction that uses line-averaged…

Numerical Analysis · Mathematics 2025-08-13 Yaqing Yang , Fengxiang Zhao , Kun Xu

In this paper we propose an algorithm for exact partitioning of high-order models. We define a general class of $m$-degree Homogeneous Polynomial Models, which subsumes several examples motivated from prior literature. Exact partitioning…

Machine Learning · Computer Science 2022-10-04 Chuyang Ke , Jean Honorio

Today's scientific simulations require a significant reduction of data volume because of extremely large amounts of data they produce and the limited I/O bandwidth and storage space. Error-bounded lossy compression has been considered one…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-05-09 Daoce Wang , Jesus Pulido , Pascal Grosset , Sian Jin , Jiannan Tian , James Ahrens , Dingwen Tao

High-order implicit shock tracking is a new class of numerical methods to approximate solutions of conservation laws with non-smooth features. These methods align elements of the computational mesh with non-smooth features to represent them…

Numerical Analysis · Mathematics 2022-02-09 Tianci Huang , Matthew J. Zahr

Graphical models with High Order Potentials (HOPs) have received considerable interest in recent years. While there are a variety of approaches to inference in these models, nearly all of them amount to solving a linear program (LP)…

Artificial Intelligence · Computer Science 2013-09-27 Elad Mezuman , Daniel Tarlow , Amir Globerson , Yair Weiss

This work introduces an optimization-based $rp$-adaptive numerical method to approximate solutions of viscous, shock-dominated flows using implicit shock tracking and a high-order discontinuous Galerkin discretization on traditionally…

Numerical Analysis · Mathematics 2025-04-22 Huijing Dong , Masayuki Yano , Tianci Huang , Matthew J. Zahr

We develop and test high-order methods for integration on surface point clouds. The task of integrating a function on a surface arises in a range of applications in engineering and the sciences, particularly those involving various integral…

Numerical Analysis · Mathematics 2026-03-12 Daniel R. Venn , Steven J. Ruuth

Traditional methods for high-dimensional diffeomorphic mapping often struggle with the curse of dimensionality. We propose a mesh-free learning framework designed for $n$-dimensional mapping problems, seamlessly combining variational…

Machine Learning · Computer Science 2025-11-05 Zhiwen Li , Cheuk Hin Ho , Lok Ming Lui

Hierarchical optimization refers to problems with interdependent decision variables and objectives, such as minimax and bilevel formulations. While various algorithms have been proposed, existing methods and analyses lack adaptivity in…

Machine Learning · Computer Science 2025-10-27 Xiaochuan Gong , Jie Hao , Mingrui Liu

In this work, we study the design and analysis of a novel hybrid high-order (HHO) method on unfitted meshes. HHO methods rely on a pair of unknowns, combining polynomials attached to the mesh faces and the mesh cells. In the unfitted…

Numerical Analysis · Mathematics 2025-10-10 Erik Burman , Alexandre Ern , Romain Mottier

An algorithm is presented for constructing high-order signed distance fields for two phase materials imaged with computed tomography. The signed distance field is high-order in that it is free of the quantization artifact associated with…

Image and Video Processing · Electrical Eng. & Systems 2021-11-03 Bryce A. Besler , Tannis D. Kemp , Nils D. Forkert , Steven K. Boyd

We present a new framework for the fast solution of inhomogeneous elliptic boundary value problems in domains with smooth boundaries. High-order solvers based on adaptive box codes or the fast Fourier transform can efficiently treat the…

Numerical Analysis · Mathematics 2025-01-31 Daniel Fortunato , David B. Stein , Alex H. Barnett

Topology optimization (TO) serves as a widely applied structural design approach to tackle various engineering problems. Nevertheless, sensitivity-based TO methods usually struggle with solving strongly nonlinear optimization problems. By…

Machine Learning · Computer Science 2025-06-16 Jun Yang , Shintaro Yamasaki

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
‹ Prev 1 4 5 6 7 8 10 Next ›