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In this paper we introduce DiffSharp, an automatic differentiation (AD) library designed with machine learning in mind. AD is a family of techniques that evaluate derivatives at machine precision with only a small constant factor of…

Mathematical Software · Computer Science 2015-11-30 Atilim Gunes Baydin , Barak A. Pearlmutter , Jeffrey Mark Siskind

Implicit time integration schemes are widely used in computational fluid dynamics numerical codes to speed-up computations. Indeed, implicit schemes usually allow for less stringent time-step stability constraints than their explicit…

Computational Physics · Physics 2019-10-23 François Fraysse , Richard Saurel

Keller-Segel systems are a set of nonlinear partial differential equations used to model chemotaxis in biology. In this paper, we propose two alternating direction implicit (ADI) schemes to solve the 2D Keller-Segel systems directly with…

Numerical Analysis · Mathematics 2026-02-11 Yubin Lu , Chi-An Chen , Xiaofan Li , Chun Liu

This study presents a novel high-order numerical method designed for solving the two-dimensional time-fractional convection-diffusion (TFCD) equation. The Caputo definition is employed to characterize the time-fractional derivative. A weak…

Numerical Analysis · Mathematics 2023-08-21 Anshima Singh , Sunil Kumar

We develop nested automatic differentiation (AD) algorithms for exact inference and learning in integer latent variable models. Recently, Winner, Sujono, and Sheldon showed how to reduce marginalization in a class of integer latent variable…

Machine Learning · Statistics 2018-06-11 Daniel Sheldon , Kevin Winner , Debora Sujono

We study the problem of preservation of maximal canards for time discretized fast-slow systems with canard fold points. In order to ensure such preservation, certain favorable structure preserving properties of the discretization scheme are…

Dynamical Systems · Mathematics 2023-03-29 Maximilian Engel , Christian Kuehn , Matteo Petrera , Yuri Suris

A linear evolving surface partial differential equation is first discretized in space by an arbitrary Lagrangian Eulerian (ALE) evolving surface finite element method, and then in time either by a Runge-Kutta method, or by a backward…

Numerical Analysis · Mathematics 2015-01-14 Balázs Kovács , Christian Andreas Power Guerra

We establish rigorous \emph{a posteriori} error bounds for a space-time finite element method of arbitrary order discretising linear wave problems in second order formulation. The method combines standard finite elements in space and…

Numerical Analysis · Mathematics 2026-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Lorenzo Mascotto , Zuodong Wang

We present goal-oriented a posteriori error estimates for the automatic variationally stable finite element (AVS FE) method for scalar-valued convection-diffusion problems. The AVS-FE method is a Petrov-Galerkin method in which the test…

Numerical Analysis · Mathematics 2021-05-12 Eirik Valseth , Albert Romkes

We demonstrate a practical differentiable programming approach for acoustic inverse problems through two applications: admittance estimation and shape optimization for resonance damping. First, we show that JAX-FEM's automatic…

Machine Learning · Computer Science 2025-11-17 Nikolas Borrel-Jensen , Josiah Bjorgaard

Reconstructing spectral functions from Euclidean Green's functions is an important inverse problem in many-body physics. However, the inversion is proved to be ill-posed in the realistic systems with noisy Green's functions. In this Letter,…

High Energy Physics - Phenomenology · Physics 2022-09-22 Lingxiao Wang , Shuzhe Shi , Kai Zhou

In this paper, we will present advanced discretization methods for solving retarded potential integral equations. We employ a $C^{\infty}$-partition of unity method in time and a conventional boundary element method for the spatial…

Numerical Analysis · Mathematics 2014-04-10 Stefan Sauter , Alexander Veit

This paper considers the numerical treatment of the time-dependent Gross-Pitaevskii equation. In order to conserve the time invariants of the equation as accurately as possible, we propose a Crank-Nicolson-type time discretization that is…

Numerical Analysis · Mathematics 2021-10-20 Patrick Henning , Johan Wärnegård

We present a unified analysis for a family of variational time discretization methods, including discontinuous Galerkin methods and continuous Galerkin-Petrov methods, applied to non-stiff initial value problems. Besides the…

Numerical Analysis · Mathematics 2021-09-17 Simon Becher , Gunar Matthies

A framework of finite-velocity model based Boltzmann equation has been developed for convection-diffusion equations. These velocities are kept flexible and adjusted to control numerical diffusion. A flux difference splitting based kinetic…

Numerical Analysis · Mathematics 2024-10-01 S. V. Raghurama Rao , K. S. Shrinath , Ankit Ruhi , Veeredhi Vasudeva Rao

This paper investigates superconvergence properties of the local discontinuous Galerkin methods with generalized alternating fluxes for one-dimensional linear convection-diffusion equations. By the technique of constructing some special…

Numerical Analysis · Mathematics 2019-12-19 Xiaobin Liu , Dazhi Zhang , Xiong Meng , Boying Wu

In this paper, we consider nonconvex decentralised optimisation and learning over a network of distributed agents. We develop an ADMM algorithm based on the Randomised Block Coordinate Douglas-Rachford splitting method which enables agents…

Optimization and Control · Mathematics 2025-07-31 Behnam Mafakheri , Jonathan H. Manton , Iman Shames

This paper discusses the upwinded local discontinuous Galerkin methods for the one-term/multi-term fractional ordinary differential equations (FODEs). The natural upwind choice of the numerical fluxes for the initial value problem for FODEs…

Numerical Analysis · Mathematics 2015-12-18 Weihua Deng , Jan S. Hesthaven

Anomalous diffusions are ubiquitous in nature, whose functional distributions are governed by the backward Feynman-Kac equation. In this paper, the local discontinuous Galerkin (LDG) method is used to solve the 2D backward Feynman-Kac…

Numerical Analysis · Mathematics 2022-06-01 Dong Liu , Weihua Deng

A characteristic feature of differential-algebraic equations is that one needs to find derivatives of some of their equations with respect to time, as part of so called index reduction or regularisation, to prepare them for numerical…

Numerical Analysis · Mathematics 2017-03-28 John D. Pryce , Nedialko S. Nedialkov , Guangning Tan , Xiao Li