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Related papers: Weak error analysis via functional It\^o calculus

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Sampling invariant distributions from an It\^o diffusion process presents a significant challenge in stochastic simulation. Traditional numerical solvers for stochastic differential equations require both a fine step size and a lengthy…

Machine Learning · Computer Science 2025-06-06 Zhiqiang Cai , Yu Cao , Yuanfei Huang , Xiang Zhou

We develop a pure Monte Carlo method to compute $E(g(X_T))$ where $g$ is a bounded and Lipschitz function and $X_t$ an Ito process. This approach extends a previously proposed method to the general multidimensional case with a SDE with…

Probability · Mathematics 2016-07-18 Mahamadou Doumbia , Nadia Oudjane , Xavier Warin

We discuss regular and weak solutions to rough partial differential equations (RPDEs), thereby providing a (rough path-)wise view on important classes of SPDEs. In contrast to many previous works on RPDEs, our definition gives honest…

Probability · Mathematics 2019-02-11 Joscha Diehl , Peter K. Friz , Wilhelm Stannat

We prove weak uniqueness for admissible solutions of It\^o's equations with uniformly nondegenerate $a$ which is almost in VMO and $b$ in a Morrey class of functions with low integrability property. If $b\in L_{d}$ any solution is…

Probability · Mathematics 2024-10-28 N. V. Krylov

For a uniform process $\{ X_t: t\in E\}$ (by which $X_t $ is uniformly distributed on $(0,1)$ for $t\in E$) and a function $w(x)>0$ on $(0,1)$, we give a sufficient condition for the weak convergence of the empirical process based on $\{…

Probability · Mathematics 2014-12-30 Yuping Yang

We propose a new method for the numerical solution of backward stochastic differential equations (BSDEs) which finds its roots in Fourier analysis. The method consists of an Euler time discretization of the BSDE with certain conditional…

Probability · Mathematics 2015-06-25 Cody Blaine Hyndman , Polynice Oyono Ngou

The combination of Monte Carlo methods and deep learning has recently led to efficient algorithms for solving partial differential equations (PDEs) in high dimensions. Related learning problems are often stated as variational formulations…

Machine Learning · Computer Science 2022-08-08 Lorenz Richter , Julius Berner

In this paper, the weak convergence about the discretization error of stochastic iterated integrals in the Skorohod sense are studied, while the integrands and integrators of iterated integrals are supposed to be semimartingales with jumps.…

Probability · Mathematics 2017-06-06 Yuping Song , Hanchao Wang

We approximate the solution of some linear systems of SDEs driven by a fractional Brownian motion $B^H$ with Hurst parameter $H\in(\frac{1}{2},1)$ in the Wick--It\^{o} sense, including a geometric fractional Brownian motion. To this end, we…

Statistics Theory · Mathematics 2010-10-11 Christian Bender , Peter Parczewski

This article discusses a unified convergence analysis of the semilinear time-dependent equation $\partial_t u + (-1)^\mathrm{m}\Delta^{\mathrm{m}}u + u^3 - u = f$ with $\mathrm{m} \in \{1,2\}$ and homogeneous Dirichlet boundary conditions.…

Analysis of PDEs · Mathematics 2026-05-12 Gopikrishnan Chirappurathu Remesan

We identify effective stochastic differential equations (SDE) for coarse observables of fine-grained particle- or agent-based simulations; these SDE then provide useful coarse surrogate models of the fine scale dynamics. We approximate the…

We obtain general weak existence and stability results for stochastic convolution equations with jumps under mild regularity assumptions, allowing for non-Lipschitz coefficients and singular kernels. Our approach relies on weak convergence…

Probability · Mathematics 2021-12-22 Eduardo Abi Jaber , Christa Cuchiero , Martin Larsson , Sergio Pulido

It is known by a formula of Hasse-Sondow that the Riemann zeta function is given, for any $ s=\sigma+it \in \mathbb{C}$, by $ \sum_{n=0}^{\infty} \widetilde{A}(n,s)$ where $$ \widetilde{A}(n,s):=\frac{1}{2^{n+1}(1-2^{1-s})} \sum_{k=0}^n…

Number Theory · Mathematics 2020-02-10 Yochay Jerby

A new class of explicit Euler schemes, which approximate stochastic differential equations (SDEs) with superlinearly growing drift and diffusion coefficients, is proposed in this article. It is shown, under very mild conditions, that these…

Probability · Mathematics 2016-09-05 Sotirios Sabanis

Soft extrapolation refers to the problem of recovering a function from its samples, multiplied by a fast-decaying window and perturbed by an additive noise, over an interval which is potentially larger than the essential support of the…

Numerical Analysis · Mathematics 2018-12-26 Dmitry Batenkov , Laurent Demanet , Hrushikesh N. Mhaskar

The numerical solution of implicit and stiff differential equations by implicit numerical integrators has been largely investigated and there exist many excellent efficient codes available in the scientific community, as Radau5 (based on a…

Numerical Analysis · Mathematics 2025-06-27 Nicola Guglielmi , Ernst Hairer

Stochastic interpolants offer a robust framework for continuously transforming samples between arbitrary data distributions, holding significant promise for generative modeling. Despite their potential, rigorous finite-time convergence…

Machine Learning · Computer Science 2025-08-12 Yuhao Liu , Rui Hu , Yu Chen , Longbo Huang

Exponential decay estimates of a general linear weakly damped wave equation are studied with decay rate lying in a range. Based on the $C^0$-conforming finite element method to discretize spatial variables keeping temporal variable…

Numerical Analysis · Mathematics 2024-06-07 P. Danumjaya , Anil Kumar , Amiya K. Pani

We investigate solutions to the functional equation $f(f(x)) = e^x$, which can be interpreted as the problem of finding a half iterate of the exponential map. While no elementary solution exists, we construct and analyze non-elementary…

Numerical Analysis · Mathematics 2025-09-30 Sanay Nesargi , Gregory Roudenko

The existence of unique solutions is established for rough differential equations (RDEs) with path-dependent coefficients and driven by c\`adl\`ag rough paths. Moreover, it is shown that the associated solution map, also known as…

Probability · Mathematics 2025-08-26 Anna P. Kwossek , Andreas Neuenkirch , David J. Prömel