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In this paper, we develop an ensemble-based time-stepping algorithm to efficiently find numerical solutions to a group of linear, second-order parabolic partial differential equations (PDEs). Particularly, the PDE models in the group could…

Numerical Analysis · Mathematics 2017-10-18 Yan Luo , Zhu Wang

We study numerical methods for the nonlinear partial differential equation that governs the motion of level sets by affine curvature. We show that standard finite difference schemes are nonlinearly unstable. We build convergent finite…

Numerical Analysis · Mathematics 2016-11-01 Adam M. Oberman , Tiago Salvador

Local constraint is closely related to the gauge field, so constrained models are usually effective low energy descriptions and important in condensed matter physics. On the other hand, local restriction hinders the application of numerical…

Statistical Mechanics · Physics 2022-10-11 Zheng Yan

A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the…

Numerical Analysis · Mathematics 2018-02-19 Yan Luo , Zhu Wang

Evaluating the performance of clustering models is a challenging task where the outcome depends on the definition of what constitutes a cluster. Due to this design, current existing metrics rarely handle multiple clustering models with…

Machine Learning · Computer Science 2025-05-08 Louis Ohl , Fredrik Lindsten

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

Solutions to conservation laws satisfy the monotonicity property: the number of local extrema is a non-increasing function of time, and local maximum/minimum values decrease/increase monotonically in time. This paper investigates this…

Numerical Analysis · Mathematics 2007-11-06 Philippe G. LeFloch , Jian-Guo Liu

This Ph.D. dissertation contains results in two different but related fields: the implementation of model predictive control (MPC) in embedded systems using first order methods, and restart schemes for accelerated first order methods…

Optimization and Control · Mathematics 2021-09-07 Pablo Krupa

We study polygonal analogues of several moving boundary problems and their time discretization which preserves the constant area speed property. We establish various polygonal analogues of geometric formulas for moving boundaries and make…

Numerical Analysis · Mathematics 2008-05-30 M. Benes , M. Kimura , S. Yazaki

The paper addresses an optimal control problem for a perturbed sweeping process of the rate-independent hysteresis type described by a controlled "play and stop" operator with separately controlled perturbations. This problem can be reduced…

Optimization and Control · Mathematics 2015-12-01 Tan H. Cao , Boris S. Mordukhovich

Standard sweep algorithms require an order of discrete points in Euclidean space, and rely on the property that, at a given point, all points in the halfspace below come earlier in this order. We are motivated by the problem of…

Computational Geometry · Computer Science 2025-10-01 Tim Ophelders , Anna Schenfisch

In this work, we propose a numerical approach for simulations of large deformations of interfaces in a level set framework. To obtain a fast and viable numerical solution in both time and space, temporal discretization is based on the…

General Mathematics · Mathematics 2023-05-30 Aymen Laadhari , Ahmad Deeb

We focus here on a class of fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. We design a novel second-order fully discrete mixed finite element method to…

Numerical Analysis · Mathematics 2020-08-28 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

In this paper we consider discrete gradient methods for approximating the solution and preserving a first integral (also called a constant of motion) of autonomous ordinary differential equations. We prove under mild conditions for a large…

Numerical Analysis · Mathematics 2013-01-22 Richard A. Norton , G. R. W. Quispel

In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent implicit fixed-point…

Numerical Analysis · Mathematics 2023-06-09 Cong Guo , Chenliang Li , Tao Luo

In the past decades, the finite difference methods for space fractional operators develop rapidly; to the best of our knowledge, all the existing finite difference schemes, including the first and high order ones, just work on uniform…

Numerical Analysis · Mathematics 2016-04-04 Lijing Zhao , Weihua Deng

On the example of the Poynting-Thomson-Zener rheological model for solids, which exhibits both dissipation and wave propagation - with nonlinear dispersion relation -, we introduce and investigate a finite difference numerical scheme. Our…

Classical Physics · Physics 2020-02-19 Tamás Fülöp , Róbert Kovács , Mátyás Szücs , Mohammad Fawaier

An algorithm for a family of self-starting high-order implicit time integration schemes with controllable numerical dissipation is proposed for both linear and nonlinear transient problems. This work builds on the previous works of the…

Numerical Analysis · Mathematics 2024-09-23 Daniel O'Shea , Xiaoran Zhang , Shayan Mohammadian , Chongmin Song

We present an accessible first course on diffusion models and flow matching for machine learning, aimed at a technical audience with no diffusion experience. We try to simplify the mathematical details as much as possible (sometimes…

Machine Learning · Computer Science 2024-06-25 Preetum Nakkiran , Arwen Bradley , Hattie Zhou , Madhu Advani

Motion segmentation is a fundamental problem in computer vision and is crucial in various applications such as robotics, autonomous driving and action recognition. Recently, spectral clustering based methods have shown impressive results on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yuxiang Huang , John Zelek
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