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Applications in quantitative finance such as optimal trade execution, risk management of options, and optimal asset allocation involve the solution of high dimensional and nonlinear Partial Differential Equations (PDEs). The connection…

Machine Learning · Statistics 2019-10-28 Batuhan Güler , Alexis Laignelet , Panos Parpas

In this article, we propose a new numerical approach to high-dimensional partial differential equations (PDEs) arising in the valuation of exotic derivative securities. The proposed method is extended from Reisinger and Wittum (2007) and…

Computational Finance · Quantitative Finance 2013-10-04 Christoph Reisinger , Rasmus Wissmann

We introduce a class of measure-valued processes, which -- in analogy to their finite dimensional counterparts -- will be called measure-valued polynomial diffusions. We show the so-called moment formula, i.e.~a representation of the…

Probability · Mathematics 2022-01-03 Christa Cuchiero , Francesco Guida , Luca di Persio , Sara Svaluto-Ferro

We consider a porous media type equation over all of $\R^d$ with $d = 1$, with monotone discontinuous coefficients with linear growth and prove a probabilistic representation of its solution in terms of an associated microscopic diffusion.…

Probability · Mathematics 2009-12-02 Philippe Blanchard , Michael Röckner , Francesco Russo

This papers deals with a construction and convergence analysis of a finite difference scheme for solving time-fractional porous medium equation. The governing equation exhibits both nonlocal and nonlinear behaviour making the numerical…

Numerical Analysis · Mathematics 2019-04-05 Łukasz Płociniczak

In this article we show that a finite dimensional stochastic differential equation driven by a L\'evy process can be formulated as a stochastic partial differential equation. We prove the existence and uniqueness of strong solutions of such…

Probability · Mathematics 2018-02-15 Suprio Bhar , Rajeev Bhaskaran , Barun Sarkar

We prove global existence and uniqueness of strong solutions to the logarithmic porous medium type equation with fractional diffusion $$ \partial_tu+(-\Delta)^{1/2}\log(1+u)=0, $$ posed for $x\in \mathbb{R}$, with nonnegative initial data…

Analysis of PDEs · Mathematics 2012-10-19 Arturo de Pablo , Fernando Quirós , Ana Rodríguez , Juan Luis Vázquez

We present a class of diffusion-based algorithms to draw samples from high-dimensional probability distributions given their unnormalized densities. Ideally, our methods can transport samples from a Gaussian distribution to a specified…

Machine Learning · Computer Science 2025-02-04 Anand Jerry George , Nicolas Macris

In this paper we further study the stochastic partial differential equation first proposed by Xiong (2013). Under localized conditions on the coefficients we show that the solution is in fact distribution-function-valued and we establish…

Probability · Mathematics 2016-10-10 Li Wang , Xu Yang , Xiaowen Zhou

Equations governing physico-chemical processes are usually known at microscopic spatial scales, yet one suspects that there exist equations, e.g. in the form of Partial Differential Equations (PDEs), that can explain the system evolution at…

Machine Learning · Statistics 2021-03-31 Hassan Arbabi , Ioannis Kevrekidis

In this work we develop a novel domain splitting strategy for the solution of partial differential equations. Focusing on a uniform discretization of the $d$-dimensional advection-diffusion equation, our proposal is a two-level algorithm…

Numerical Analysis · Mathematics 2023-03-03 Ken Trotti

We introduce the multivariate decomposition finite element method (MDFEM) for solving elliptic PDEs with uniform random diffusion coefficients. We show that the MDFEM can be used to reduce the computational complexity of estimating the…

Numerical Analysis · Mathematics 2021-07-28 Dong T. P. Nguyen , Dirk Nuyens

In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the…

Numerical Analysis · Mathematics 2014-07-02 Victor Calo , Yalchin Efendiev , Juan Galvis , Mehdi Ghommem

A novel global energy model for multi-class semantic image segmentation is proposed that admits very efficient exact inference and derivative calculations for learning. Inference in this model is equivalent to MAP inference in a particular…

Computer Vision and Pattern Recognition · Computer Science 2016-04-04 Paul Vernaza

We discuss a Bayesian formulation to coarse-graining (CG) of PDEs where the coefficients (e.g. material parameters) exhibit random, fine scale variability. The direct solution to such problems requires grids that are small enough to resolve…

Machine Learning · Statistics 2019-09-10 Constantin Grigo , Phaedon-Stelios Koutsourelakis

The paper is devoted to the numerical solutions of fractional PDEs based on its probabilistic interpretation, that is, we construct approximate solutions via certain Monte Carlo simulations. The main results represent the upper bound of…

Probability · Mathematics 2020-12-29 Vassili Kolokoltsov , Feng Lin , Aleksandar Mijatovic

This paper presents new geometric aspects of the behaviors of solutions to the porous medium equation (PME) and its associated equation. First we discuss the Legendre structure with information geometry on the manifold of generalized…

Statistical Mechanics · Physics 2009-12-16 Atsumi Ohara , Tatsuaki Wada

We consider a possibly degenerate porous media type equation over all of $\R^d$ with $d = 1$, with monotone discontinuous coefficients with linear growth and prove a probabilistic representation of its solution in terms of an associated…

Probability · Mathematics 2014-06-30 Viorel Barbu , Michael Roeckner , Francesco Russo

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon…

Numerical Analysis · Mathematics 2016-03-30 X. Feng , J. Lin. , C. Lorton

The Fractional Diffusion Equation (FDE) is a mathematical model that describes anomalous transport phenomena characterized by non-local and long-range dependencies which deviate from the traditional behavior of diffusion. Solving this…

Numerical Analysis · Mathematics 2023-11-14 Mohammad Partohaghighi , Emmanuel Asante-Asamani , Olaniyi S. Iyiola