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The coupled system, where one is a degenerate parabolic equation and the other has not a diffusion term arises in the modeling of European options with liquidity shocks. Two implicit-explicit (IMEX) schemes that preserve the positivity of…

Computational Finance · Quantitative Finance 2015-04-01 W. Mudzimbabwe , Lubin G. Vulkov

Time integration methods for solving initial value problems are an important component of many scientific and engineering simulations. Implicit time integrators are desirable for their stability properties, significantly relaxing…

Numerical Analysis · Mathematics 2020-11-24 Ross Glandon , Mahesh Narayanamurthi , Adrian Sandu

First-order fully implicit as well as implicit--explicit schemes for coupled elliptic-parabolic systems are discussed in [Ern and Meunier, ESAIM: M2AN, 2009] and [Altmann et al., Math.\ Comp., 2021], respectively. The extension of the…

Numerical Analysis · Mathematics 2026-01-06 Georgios Akrivis , Minghua Chen , Fan Yu

This paper presents an a priori error analysis of the Deep Mixed Residual method (MIM) for solving high-order elliptic equations with non-homogeneous boundary conditions, including Dirichlet, Neumann, and Robin conditions. We examine MIM…

Numerical Analysis · Mathematics 2024-11-26 Mengjia Bai , Jingrun Chen , Rui Du , Zhiwei Sun

We consider the development of high order asymptotic-preserving linear multistep methods for kinetic equations and related problems. The methods are first developed for BGK-like kinetic models and then extended to the case of the full…

Numerical Analysis · Mathematics 2016-03-06 Giacomo Dimarco , Lorenzo Pareschi

Peer methods are a comprehensive class of time integrators offering numerous degrees of freedom in their coefficient matrices that can be used to ensure advantageous properties, e.g. A-stability or super-convergence. In this paper, we show…

Numerical Analysis · Mathematics 2020-10-27 Moritz Schneider , Jens Lang

Integral deferred correction (IDC) methods have been shown to be an efficient way to achieve arbitrary high order accuracy and possess good stability properties. In this paper, we construct high order operator splitting schemes using the…

Numerical Analysis · Mathematics 2015-05-20 Andrew J. Christlieb , Yuan Liu , Zhengfu Xu

In this paper, we develop a class of high-order conservative methods for simulating non-equilibrium radiation diffusion problems. Numerically, this system poses significant challenges due to strong nonlinearity within the stiff source terms…

Numerical Analysis · Mathematics 2024-01-30 Shaoqin Zheng , Min Tang , Qiang Zhang , Tao Xiong

A simple iterative approach for solving a set of implicit kinetic moment equations is proposed. This implicit solve is a key component in the IMEX discretization of the multi-species Bhatnagar-Gross-Krook (M-BGK) model with nontrivial…

Numerical Analysis · Mathematics 2024-04-30 Evan Habbershaw , Cory D. Hauck , Steven M. Wise

In this paper, we propose a high-order domain decomposition method for the ES-BGK model of the Boltzmann equation, which dynamically detects regions of equilibrium and non-equilibrium. Our implementation automatically switches between Euler…

Numerical Analysis · Mathematics 2025-12-04 Domenico Caparello , Tommaso Tenna

We propose an optimization proxy in terms of iterative implicit gradient methods for solving constrained optimization problems with nonconvex loss functions. This framework can be applied to a broad range of machine learning settings,…

Optimization and Control · Mathematics 2025-10-14 Harshal D. Kaushik , Ming Jin

For solving linear ill-posed problems regularization methods are required when the right hand side is with some noise. In the present paper regularized solutions are obtained by implicit iteration methods in Hilbert scales. % By exploiting…

Numerical Analysis · Mathematics 2015-05-20 Qinian Jin , Ulrich Tautenhahn

We introduce a new class of arbitrary-order exponential time differencing methods based on spectral deferred correction (ETDSDC) and describe a simple procedure for initializing the requisite matrix functions. We compare the stability and…

Numerical Analysis · Mathematics 2020-11-03 Tommaso Buvoli

A non-uniform implicit-explicit L1 mixed finite element method (IMEX-L1-MFEM) is investigated for a class of time-fractional partial integro-differential equations (PIDEs) with space-time dependent coefficients and non-self-adjoint elliptic…

Numerical Analysis · Mathematics 2024-11-05 Lok Pati Tripathi , Aditi Tomar , Amiya K. Pani

Explicit step-truncation tensor methods have recently proven successful in integrating initial value problems for high-dimensional partial differential equations (PDEs). However, the combination of non-linearity and stiffness may introduce…

Numerical Analysis · Mathematics 2023-03-21 Abram Rodgers , Daniele Venturi

Stiff systems of ordinary differential equations (ODEs) arise in a wide range of scientific and engineering disciplines and are traditionally solved using implicit integration methods due to their stability and efficiency. However, these…

Numerical Analysis · Mathematics 2024-12-02 Colby Fronk , Linda Petzold

In this paper, a new implicit-explicit local method with an arbitrary order is produced for stiff initial value problems. Here, a general method for one-step time integrations has been created, considering a direction free approach for…

Numerical Analysis · Mathematics 2021-04-14 Huseyin Tunc , Murat Sari

Implicit-explicit (IMEX) Runge-Kutta methods play a major rule in the numerical treatment of differential systems governed by stiff and non-stiff terms. This paper discusses order conditions and symplecticity properties of a class of IMEX…

Numerical Analysis · Mathematics 2012-02-07 Michael Herty , Lorenzo Pareschi , Sonja Steffensen

Fast and accurate solution of time-dependent partial differential equations (PDEs) is of key interest in many research fields including physics, engineering, and biology. Generally, implicit schemes are preferred over the explicit ones for…

Numerical Analysis · Mathematics 2019-11-28 Suprosanna Shit , Abinav Ravi Venkatakrishnan , Ivan Ezhov , Jana Lipkova , Marie Piraud , Bjoern Menze

Continual learning (CL) remains one of the long-standing challenges for deep neural networks due to catastrophic forgetting of previously acquired knowledge. Although rehearsal-based approaches have been fairly successful in mitigating…

Machine Learning · Computer Science 2024-04-30 Prashant Bhat , Bharath Renjith , Elahe Arani , Bahram Zonooz
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