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In this paper we investigate a priori error estimates for the space-time Galerkin finite element discretization of a simplified semilinear gradient enhanced damage model. The model equations are of a special structure as the state equation…

Optimization and Control · Mathematics 2020-04-14 Marita Holtmannspötter , Arnd Rösch

We derive a second-order ordinary differential equation (ODE) which is the limit of Nesterov's accelerated gradient method. This ODE exhibits approximate equivalence to Nesterov's scheme and thus can serve as a tool for analysis. We show…

Machine Learning · Statistics 2015-10-29 Weijie Su , Stephen Boyd , Emmanuel J. Candes

Uncertainty is unavoidable in modeling dynamical systems and it may be represented mathematically by differential inclusions. In the past, we proposed an algorithm to compute validated solutions of differential inclusions; here we provide…

Numerical Analysis · Mathematics 2020-01-31 Sanja Zivanovic Gonzalez , Pieter Collins , Luca Geretti , Davide Bresolin , Tiziano Villa

Machine learned partial differential equation (PDE) solvers trade the reliability of standard numerical methods for potential gains in accuracy and/or speed. The only way for a solver to guarantee that it outputs the exact solution is to…

Numerical Analysis · Mathematics 2023-03-30 Nick McGreivy , Ammar Hakim

The increasing demand for electricity and the aging infrastructure of power distribution systems have raised significant concerns about future system reliability. Failures in distribution systems, closely linked to system usage and…

Optimization and Control · Mathematics 2024-10-21 Gejia Zhang , Robert Mieth

Within recent years, considerable progress has been made regarding high-performance solvers for Partial Differential Equations (PDEs), yielding potential gains in efficiency compared to industry standard tools. However, the latter largely…

Numerical Analysis · Mathematics 2024-02-20 Patrick Zimbrod , Michael Fleck , Johannes Schilp

ADER schemes are numerical methods, which can reach an arbitrary order of accuracy in both space and time. They are based on a reconstruction procedure and the solution of generalized Riemann problems. However, for general boundary…

Numerical Analysis · Computer Science 2016-06-10 Gino I. Montecinos

We show that the Discrete Exterior Calculus (DEC) method can be cast as the earlier box method for the Poisson problem in the plane. Consequently, error estimates are established, proving that the DEC method is comparable to the Finite…

Numerical Analysis · Mathematics 2019-07-17 Ruben Carrillo , Miguel Angel Moreles , Rafael Herrera

Encoder-decoder transformer models have achieved great success on various vision-language (VL) tasks, but they suffer from high inference latency. Typically, the decoder takes up most of the latency because of the auto-regressive decoding.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Peng Tang , Pengkai Zhu , Tian Li , Srikar Appalaraju , Vijay Mahadevan , R. Manmatha

This paper is concerned with the PDE and numerical analysis of a modified one-dimensional intravascular stent model originally proposed in [4]. It is proved that the modified model has a unique weak solution using the Galerkin method…

Numerical Analysis · Mathematics 2024-04-23 Xiaobing Feng , Tingao Jiang

In this paper, we develop a novel accelerated fixed-point-based framework using delayed inexact oracles to approximate a fixed point of a nonexpansive operator (or equivalently, a root of a co-coercive operator), a central problem in…

Optimization and Control · Mathematics 2025-12-16 Nghia Nguyen-Trung , Quoc Tran-Dinh

We present an arbitrarily high-order, conditionally stable, partitioned spectral deferred correction (SDC) method for solving multiphysics problems using a sequence of pre-existing single-physics solvers. This method extends the work in [1,…

Numerical Analysis · Mathematics 2020-04-07 Daniel Z. Huang , Will Pazner , Per-Olof Persson , Matthew J. Zahr

We provide a novel accelerated first-order method that achieves the asymptotically optimal convergence rate for smooth functions in the first-order oracle model. To this day, Nesterov's Accelerated Gradient Descent (AGD) and variations…

Optimization and Control · Mathematics 2018-02-13 Jelena Diakonikolas , Lorenzo Orecchia

The Parareal algorithm is used to solve time-dependent problems considering multiple solvers that may work in parallel. The key feature is a initial rough approximation of the solution that is iteratively refined by the parallel solvers. We…

Systems and Control · Computer Science 2014-02-18 Loïc Michel

Neural Ordinary Differential Equations (ODEs) represent a significant advancement at the intersection of machine learning and dynamical systems, offering a continuous-time analog to discrete neural networks. Despite their promise, deploying…

Numerical Analysis · Mathematics 2025-06-18 Matteo Caldana , Jan S. Hesthaven

In the present paper we consider a 2-D shallow-water equations (SWE) model on a $\beta$-plane solved using an alternating direction fully implicit (ADI) finite-difference scheme on a rectangular domain. The scheme was shown to be…

Computational Physics · Physics 2015-06-12 Razvan Stefanescu , Ionel Michael Navon

We propose two new alternative numerical schemes to solve the coupled Einstein-Euler equations in the Generalized Harmonic formulation. The first one is a finite difference (FD) Central Weighted Essentially Non-Oscillatory (CWENO) scheme on…

Numerical Analysis · Mathematics 2026-05-12 Stefano Muzzolon , Michael Dumbser , Olindo Zanotti , Elena Gaburro

We establish a discrete operator--theoretic framework for the analysis of implicit Euler and Lie--Trotter splitting schemes for delay differential equations (DDEs). Both schemes are formulated in terms of discrete resolvent operators acting…

Optimization and Control · Mathematics 2026-03-03 Hideki Kawahara

Partial differential equation (PDE) foundation models are pretrained networks that forecast how physical fields like velocity and pressure evolve from a single reusable solver. On unfamiliar flows their predictions drift step by step,…

Machine Learning · Computer Science 2026-05-26 Chengze Li , Lingwei Wei , Li Sun , Hongbo Lv , Jie Yang , Hanrong Zhang , Kening Zheng , Wei-Chieh Huang , Enze Ma , Philip S. Yu

We are interested in the numerical solution of coupled nonlinear partial differential equations (PDEs) in two and three dimensions. Under certain assumptions on the domain, we take advantage of the Kronecker structure arising in standard…

Numerical Analysis · Mathematics 2021-07-21 Gerhard Kirsten
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