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In this paper, a few dual least-squares finite element methods and their application to scalar linear hyperbolic problems are studied. The purpose is to obtain $L^2$-norm approximations on finite element spaces of the exact solutions to…

Numerical Analysis · Mathematics 2020-10-06 Delyan Z. Kalchev , Thomas A. Manteuffel , Steffen Münzenmaier

In some recent works [G. Dimarco, L. Pareschi, Hybrid multiscale methods I. Hyperbolic Relaxation Problems, Comm. Math. Sci., 1, (2006), pp. 155-177], [G. Dimarco, L. Pareschi, Hybrid multiscale methods II. Kinetic equations, SIAM…

Numerical Analysis · Mathematics 2011-02-07 Giacomo Dimarco , Lorenzo Pareschi

We consider the numerical construction of minimal Lagrangian graphs, which is related to recent applications in materials science, molecular engineering, and theoretical physics. It is known that this problem can be formulated as an…

Numerical Analysis · Mathematics 2021-07-01 Brittany Froese Hamfeldt , Jacob Lesniewski

Stochastic PDEs of Fluctuating Hydrodynamics are a powerful tool for the description of fluctuations in many-particle systems. In this paper, we develop and analyze a Multilevel Monte Carlo (MLMC) scheme for the Dean--Kawasaki equation, a…

Numerical Analysis · Mathematics 2024-05-09 Federico Cornalba , Julian Fischer

In this paper, a nonlinear system of fractional ordinary differential equations with multiple scales in time is investigated. We are interested in the effective long-term computation of the solution. The main challenge is how to obtain the…

Numerical Analysis · Mathematics 2022-01-07 Zhaoyang Wang , Ping Lin

In this paper we derive semi-closed form prices of barrier (perhaps, time-dependent) options for the Hull-White model, ie., where the underlying follows a time-dependent OU process with a mean-reverting drift. Our approach is similar to…

Computational Finance · Quantitative Finance 2020-09-21 Andrey Itkin , Dmitry Muravey

Distributed learning methods have gained substantial momentum in recent years, with communication overhead often emerging as a critical bottleneck. Gradient compression techniques alleviate communication costs but involve an inherent…

Machine Learning · Computer Science 2025-07-09 Ze'ev Zukerman , Bassel Hamoud , Kfir Y. Levy

Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in control theory, and derivative prices in finance. It is often…

Machine Learning · Computer Science 2024-07-18 Xingzi Xu , Ali Hasan , Jie Ding , Vahid Tarokh

Variational quantum algorithms are a promising tool for solving partial differential equations. The standard approach for its numerical solution are finite difference schemes, which can be reduced to the linear algebra problem. We consider…

Quantum Physics · Physics 2023-10-10 N. M. Guseynov , A. A. Zhukov , W. V. Pogosov , A. V. Lebedev

Mixed Integer Programming (MIP) has been extensively applied in areas requiring mathematical solvers to address complex instances within tight time constraints. However, as the problem scale increases, the complexity of model formulation…

Computation and Language · Computer Science 2024-09-19 Teng Wang , Wing-Yin Yu , Ruifeng She , Wenhan Yang , Taijie Chen , Jianping Zhang

Conservation laws in the form of elliptic and parabolic partial differential equations (PDEs) are fundamental to the modeling of many problems such as heat transfer and flow in porous media. Many of such PDEs are stochastic due to the…

Computational Physics · Physics 2018-11-19 Amir H. Delgoshaie , Peter W. Glynn , Patrick Jenny , Hamdi A. Tchelepi

This paper introduces a novel approach for the construction of bulk--surface splitting schemes for semi-linear parabolic partial differential equations with dynamic boundary conditions. The proposed construction is based on a reformulation…

Numerical Analysis · Mathematics 2023-07-06 R. Altmann , C. Zimmer

We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms…

Numerical Analysis · Mathematics 2024-06-04 Leticia Mattos Da Silva , Oded Stein , Justin Solomon

In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice,…

Computation · Statistics 2017-02-07 Alexandros Beskos , Ajay Jasra , Kody Law , Raul Tempone , Yan Zhou

We present a simple and easy to implement method for the numerical solution of a rather general class of Hamilton-Jacobi-Bellman (HJB) equations. In many cases, the considered problems have only a viscosity solution, to which, fortunately,…

Computational Finance · Quantitative Finance 2011-02-17 Jan Hendrik Witte , Christoph Reisinger

Differential ML (Huge and Savine 2020) is a technique for training neural networks to provide fast approximations to complex simulation-based models for derivatives pricing and risk management. It uses price sensitivities calculated through…

Pricing of Securities · Quantitative Finance 2026-04-23 Paul Glasserman , Siddharth Hemant Karmarkar

This paper comprehensively reviews the application of machine learning (ML) and AI in finance, specifically in the context of asset pricing. It starts by summarizing the traditional asset pricing models and examining their limitations in…

Statistical Finance · Quantitative Finance 2024-03-12 Junyi Ye , Bhaskar Goswami , Jingyi Gu , Ajim Uddin , Guiling Wang

When using boundary integral equation methods, we represent solutions of a linear partial differential equation as layer potentials. It is well-known that the approximation of layer potentials using quadrature rules suffer from poor…

Numerical Analysis · Mathematics 2021-09-24 Camille Carvalho

An implicit finite difference method with non-uniform timesteps for solving the fractional diffusion equation in the Caputo form is proposed. The method allows one to build adaptive methods where the size of the timesteps is adjusted to the…

Numerical Analysis · Mathematics 2024-06-28 Santos B. Yuste , Joaquín Quintana-Murillo

Most results in multifractal analysis are obtained using either a thermodynamic approach based on existence and uniqueness of equilibrium states or a saturation approach based on some version of the specification property. A general…

Dynamical Systems · Mathematics 2019-02-20 Vaughn Climenhaga