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Regularizing the optimal transport (OT) problem has proven crucial for OT theory to impact the field of machine learning. For instance, it is known that regularizing OT problems with entropy leads to faster computations and better…

Machine Learning · Statistics 2020-08-04 François-Pierre Paty , Marco Cuturi

We describe along the guidelines of Kohn "Quantitative estimates..." (1999), the constant E_s which is needed to control the commutator of a totally real vector field T with di-bar* in order to have Sobolev s-regularity of the Bergman…

Complex Variables · Mathematics 2011-09-14 Stefano Pinton , Giuseppe Zampieri

In this article, we extend a Milstein finite difference scheme introduced in [Giles & Reisinger(2011)] for a certain linear stochastic partial differential equation (SPDE), to semi- and fully implicit timestepping as introduced by…

Numerical Analysis · Mathematics 2012-08-03 Christoph Reisinger

The numerical approximation of partial differential equations (PDEs) poses formidable challenges in high dimensions since classical grid-based methods suffer from the so-called curse of dimensionality. Recent attempts rely on a combination…

Machine Learning · Computer Science 2023-07-31 Lorenz Richter , Leon Sallandt , Nikolas Nüsken

We consider a model initial- and Dirichlet boundary- value problem for a fourth-order linear stochastic parabolic equation, in one space dimension, forced by an additive space-time white noise. First, we approximate its solution by the…

Numerical Analysis · Mathematics 2016-07-19 Georgios E. Zouraris

In this article we study effects that small perturbations in the noise have to the solution of differential equations driven by H\"older continuous functions of order $H>\frac12$. As an application, we consider stochastic differential…

Probability · Mathematics 2020-05-11 Lauri Viitasaari , Caibin Zeng

This work is a continuation of [E. Bonnetier, D.Bresch, V. Milisic, submitted]; it deals with rough boundaries in the simplified context of a Poisson equation. We impose Dirichlet boundary conditions on the periodic microscopic perturbation…

Analysis of PDEs · Mathematics 2008-12-24 Vuk Milisic

This paper investigates weighted mixed-norm estimates for divergence-type parabolic equations on Reifenberg-flat domains with the conormal derivative boundary condition. The leading coefficients are assumed to be merely measurable in the…

Analysis of PDEs · Mathematics 2025-10-27 Hongjie Dong , Pilgyu Jung , Doyoon Kim

We prove weighted Orlicz-Sobolev regularity for fully nonlinear elliptic equations with oblique boundary condition under asymptotic conditions of the following problem: $F(D^{2}u,Du,u,x)=f(x)$ in the bounded domain $\Omega\subset…

Analysis of PDEs · Mathematics 2023-12-14 Junior da S. Bessa

We prove a regularity result for the Poisson problem $-\Delta u = f$, $u |\_{\pa \PP} = g$ on a polyhedral domain $\PP \subset \RR^3$ using the \BK\ spaces $\Kond{m}{a}(\PP)$. These are weighted Sobolev spaces in which the weight is given…

Analysis of PDEs · Mathematics 2015-10-28 Bernd Ammann , Victor Nistor

We analyse a posteriori error estimates for the discretization with mixed finite elements on simplicial or Cartesian meshes of the multigroup neutron simplified transport (SPN ) equations, in the case where a Robin (or Fourier type)…

Numerical Analysis · Mathematics 2026-04-06 Patrick Ciarlet , Minh-Hieu Do , Mario Gervais , François Madiot

We introduce a priori Sobolev-space error estimates for the solution of nonlinear, and possibly parametric, PDEs using Gaussian process and kernel based methods. The primary assumptions are: (1) a continuous embedding of the reproducing…

Numerical Analysis · Mathematics 2023-05-10 Pau Batlle , Yifan Chen , Bamdad Hosseini , Houman Owhadi , Andrew M Stuart

We derive a posteriori error estimates for a fully discrete time-implicit finite element approximation of the stochastic total variaton flow (STVF) with additive space time noise. The estimates are first derived for an implementable fully…

Numerical Analysis · Mathematics 2022-11-09 Ľubomír Baňas , André Wilke

The robust low-rank tensor completion problem addresses the challenge of recovering corrupted high-dimensional tensor data with missing entries, outliers, and sparse noise commonly found in real-world applications. Existing methodologies…

Machine Learning · Statistics 2026-04-16 Biswarup Karmakar , Ratikanta Behera

The paper proves existence of renormalized stationary solutions for a dense class of discrete velocity Boltzmann equations in the plane with given ingoing boundary values. The proof is based on the construction of a sequence of…

Mathematical Physics · Physics 2021-12-17 L. Arkeryd , A. Nouri

We consider a quasilinear parabolic stochastic partial differential equation driven by a multiplicative noise and study regularity properties of its weak solution satisfying classical a priori estimates. In particular, we determine…

Numerical Analysis · Mathematics 2015-03-13 Arnaud Debussche , Sylvain De Moor , Martina Hofmanova

Identification of nonlinear dynamical systems is crucial across various fields, facilitating tasks such as control, prediction, optimization, and fault detection. Many applications require methods capable of handling complex systems while…

Machine Learning · Statistics 2024-11-05 Luc Brogat-Motte , Riccardo Bonalli , Alessandro Rudi

Mixed optimal stopping and stochastic control problems define variational inequalities with non-linear Hamilton-Jacobi-Bellman (HJB) operators, whose numerical solution is notoriously difficult and lack of reliable benchmarks. We first use…

Optimization and Control · Mathematics 2025-05-27 Yun Zhao , Harry Zheng

We establish the existence of solutions to common noise McKean-Vlasov martingale problems for coefficients with low regularity. Our approach is able to handle the key challenge posed by drift coefficients that are discontinuous with respect…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

In this paper we introduce concepts from uncertainty quantification (UQ) and numerical analysis for the efficient evaluation of stochastic high dimensional Newton iterates. In particular, we develop complex analytic regularity theory of the…

Numerical Analysis · Mathematics 2019-05-23 Julio Enrique Castrillon-Candas , Mark Kon