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Numerical resolution of high-dimensional nonlinear PDEs remains a huge challenge due to the curse of dimensionality. Starting from the weak formulation of the Lawson-Euler scheme, this paper proposes a stochastic particle method (SPM) by…

Numerical Analysis · Mathematics 2025-02-11 Zhengyang Lei , Sihong Shao , Yunfeng Xiong

We introduce mixed model trace regression (MMTR), a mixed model linear regression extension for scalar responses and high-dimensional matrix-valued covariates. MMTR's fixed effects component is equivalent to trace regression, with an…

Methodology · Statistics 2025-03-19 Ian Hultman , Sanvesh Srivastava

The challenge of approximating functions in infinite-dimensional spaces from finite samples is widely regarded as formidable. We delve into the challenging problem of the numerical approximation of Sobolev-smooth functions defined on…

Optimization and Control · Mathematics 2024-10-11 Massimo Fornasier , Pascal Heid , Giacomo Enrico Sodini

We investigate the regularity of the law of Wong-Zakai-type approximations for It\^o stochastic differential equations. These approximations solve random differential equations where the diffusion coefficient is Wick-multiplied by the…

Probability · Mathematics 2019-01-10 Alberto Lanconelli

In this paper, we study the Dirichlet boundary value problem of steady-state relativistic Boltzmann equation in half-line with hard potential model, given the data for the outgoing particles at the boundary and a relativistic global…

Analysis of PDEs · Mathematics 2024-11-12 Yi Wang , Li Li , Zaihong Jiang

The squared Wasserstein distance is a natural quantity to compare probability distributions in a non-parametric setting. This quantity is usually estimated with the plug-in estimator, defined via a discrete optimal transport problem which…

Optimization and Control · Mathematics 2020-10-30 Lenaic Chizat , Pierre Roussillon , Flavien Léger , François-Xavier Vialard , Gabriel Peyré

In this work, we demonstrate the Wong-Zakai approximation results for two and three dimensional stochastic convective Brinkman-Forchheimer (SCBF) equations forced by Hilbert space valued Wiener noise on bounded domains. Even though the…

Probability · Mathematics 2022-02-24 Kush Kinra , Manil T. Mohan

In this paper we provide key estimates used in the stability and error analysis of discontinuous Galerkin finite element methods (DGFEMs) on domains with curved boundaries. In particular, we review trace estimates, inverse estimates,…

Numerical Analysis · Mathematics 2019-04-02 Ellya L. Kawecki

We consider a 2D stochastic modified Swift-Hohenberg equations with multiplicative noise and periodic boundary. First, we establish the existence of local and global martingale and pathwise solutions in the regular Sobolev space $H^{2m}$…

Dynamical Systems · Mathematics 2024-04-24 Jintao Wang , Xiaoqian Zhang , Chunqiu Li

This article is concerned with the well-posedness of the "filtering equations", due to Zakai and Kushner-Stratonovich, arising in nonlinear stochastic filtering. In general situations, notably in correlated diffusion models and when signal…

Probability · Mathematics 2026-02-02 Fabio Bugini , Peter K. Friz , Khoa Lê , Huilin Zhang

This paper deals with a priori pointwise error estimates for the finite element solution of boundary value problems with Neumann boundary conditions in polygonal domains. Due to the corners of the domain, the convergence rate of the…

Numerical Analysis · Mathematics 2018-05-01 Thomas Apel , Johannes Pfefferer , Sergejs Rogovs , Max Winkler

We study the regularity in weighted Sobolev spaces of Schr\"{o}dinger-type eigenvalue problems, and we analyse their approximation via a discontinuous Galerkin (dG) $hp$ finite element method. In particular, we show that, for a class of…

Numerical Analysis · Mathematics 2019-12-17 Yvon Maday , Carlo Marcati

We formulate an initial- and Dirichlet boundary- value problem for a linear stochastic heat equation, in one space dimension, forced by an additive space-time white noise. First, we approximate the mild solution to the problem by the…

Numerical Analysis · Mathematics 2017-09-26 Georgios E. Zouraris

By using a simple observation that the density processes appearing in Ito's martingale representation theorem are invariant under the change of measures, we establish a non-linear version of the Cameron-Martin formula for solutions of a…

Probability · Mathematics 2010-11-16 G. Liang , A. Lionnet , Z. Qian

Multidimensional function data arise from many fields nowadays. The covariance function plays an important role in the analysis of such increasingly common data. In this paper, we propose a novel nonparametric covariance function estimation…

Methodology · Statistics 2021-09-14 Jiayi Wang , Raymond K. W. Wong , Xiaoke Zhang

We provide a novel -- and to the best of our knowledge, the first -- algorithm for high dimensional sparse regression with constant fraction of corruptions in explanatory and/or response variables. Our algorithm recovers the true sparse…

Machine Learning · Computer Science 2019-05-31 Liu Liu , Yanyao Shen , Tianyang Li , Constantine Caramanis

The stability and convergence analysis of high-order numerical approximations for the one- and two-dimensional nonlocal wave equations on unbounded spatial domains are considered. We first use the quadrature-based finite difference schemes…

Numerical Analysis · Mathematics 2022-11-09 Jihong Wang , Jerry Zhijian Yang , Jiwei Zhang

We investigate the regularity issue for the diffuse reflection boundary problem to the stationary linearized Boltzmann equation for hard sphere potential, cutoff hard potential, or cutoff Maxwellian molecular gases in a strictly convex…

Analysis of PDEs · Mathematics 2018-03-13 I-Kun Chen , Chun-Hsiung Hsia , Daisuke Kawagoe

This paper derives a Ziv-Zakai Bound (ZZB) on the Mean Squared Error (MSE) for Direction-of-Arrival (DoA) estimation in co-located Multiple-Input Multiple-Output (MIMO) radar systems and provides closed-form expressions that hold for…

Information Theory · Computer Science 2025-11-12 Mohammadreza Bakhshizadeh Mohajer , Daniela Tuninetti , Luca Barletta

Entropic regularization is quickly emerging as a new standard in optimal transport (OT). It enables to cast the OT computation as a differentiable and unconstrained convex optimization problem, which can be efficiently solved using the…

Machine Learning · Statistics 2018-02-21 Mathieu Blondel , Vivien Seguy , Antoine Rolet
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