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As a generalization to the heat semigroup on the Heisenberg group, the diffusion semigroup generated by the subelliptic operator $L:=\ff 1 2 \sum_{i=1}^m X_i^2$ on $\R^{m+d}:= \R^m\times\R^d$ is investigated, where $$X_i(x,y)= \sum_{k=1}^m…

Probability · Mathematics 2014-04-15 Feng-Yu Wang

In this paper, we study a multidimensional backward stochastic differential equation (BSDE) with an additional rough drift (rough BSDE), and give the existence and uniqueness of the adapted solution, either when the terminal value and the…

Probability · Mathematics 2024-01-12 Jiahao Liang , Shanjian Tang

Inverse problems in scientific computing often require optimization over infinite-dimensional Hilbert spaces. A commonly used solver in such settings is stochastic gradient descent (SGD), where gradients are approximated using randomly…

Optimization and Control · Mathematics 2026-04-14 Sandra Cerrai , Qin Li , Anjali Nair , Jaeyoung Yoon

We characterize all semigroups sandwiched between the semigroup of a Dirichlet form and the semigroup of its active main part. In case the Dirichlet form is regular, we give a more explicit description of the quadratic forms of the…

Functional Analysis · Mathematics 2023-01-04 Matthias Keller , Daniel Lenz , Marcel Schmidt , Michael Schwarz , Melchior Wirth

In this paper, we consider the Dirichlet boundary value problem for fully nonlinear Yamabe equations on Riemannian manifolds with boundary. Assuming the existence of a subsolution, we derive \emph{a priori} boundary second derivative…

Analysis of PDEs · Mathematics 2025-11-04 Weisong Dong , Yanyan Li , Luc Nguyen

A method for obtaining discretization formulas for the derivatives of a function is presented, which relies on a generalization of divided differences. These modified divided differences essentially correspond to a change of the dependent…

Computational Physics · Physics 2026-02-03 Alexander Pikovski

We formulate a well-posedness and approximation theory for a class of generalised saddle point problems with a specific form of constraints. In this way we develop an approach to a class of fourth order elliptic partial differential…

Numerical Analysis · Mathematics 2021-03-26 Charles M. Elliott , Philip J. Herbert

We establish H\"older regularity and gradient estimates for the transition semigroup of the solutions to the following SDE: $$ {\rm d} X_t=\sigma (t, X_{t-}){\rm d} Z_t+b (t, X_t){\rm d} t,\ \ X_0=x\in{\mathbb R}^d, $$ where $( Z_t)_{t\geq…

Probability · Mathematics 2020-01-14 Zhen-Qing Chen , Zimo Hao , Xicheng Zhang

Semigroups, generated by Feller processes killed upon leaving a given domain, are considered. These semigroups correspond to Cauchy-Dirichlet type initial-exterior value problems in this domain for a class of evolution equations with…

Probability · Mathematics 2021-03-08 Yana A. Butko

The work is devoted to Dirichlet problem for sub-quintic semi-linear wave equation with damping damping term of the form $(-\Delta)^\alpha\partial_t u$, $\alpha\in(0,\frac{1}{2})$, in bounded smooth domains of $\Bbb R^3$. It appears that to…

Analysis of PDEs · Mathematics 2014-03-31 Anton Savostianov

In this work, we derive sharp non-asymptotic deviation bounds for weighted sums of Dirichlet random variables. These bounds are based on a novel integral representation of the density of a weighted Dirichlet sum. This representation allows…

Probability · Mathematics 2023-04-07 Denis Belomestny , Pierre Menard , Alexey Naumov , Daniil Tiapkin , Michal Valko

We propose a tractable semiparametric estimation method for structural dynamic discrete choice models. The distribution of additive utility shocks in the proposed framework is modeled by location-scale mixtures of extreme value…

Econometrics · Economics 2023-08-15 Andriy Norets , Kenichi Shimizu

Various sharp pointwise estimates for the gradient of solutions to the heat equation are obtained. The Dirichlet and Neumann conditions are prescribed on the boundary of a half-space. All data belong to the Lebesgue space $L^p$. Derivation…

Analysis of PDEs · Mathematics 2018-08-10 Gershon Kresin , Vladimir Maz'ya

We prove the existence and a new representation formula for the gradient of the semigroup associated to an Ornstein-Uhlenbeck in a bounded convex domain in d dimensions.

Analysis of PDEs · Mathematics 2021-07-07 Giuseppe Da Prato , Luciano Tubaro

In this paper we obtain interior regularity estimates for viscosity solutions of nonlocal Dirichlet problems that degenerate when the gradient of the solution vanishes. Interior H\"older estimates are obtained when the order of the…

Analysis of PDEs · Mathematics 2020-04-08 Disson Dos Prazeres , Erwin Topp

In this paper we propose new insights and ideas to set up quantitative boundary estimates for solutions to Dirichlet problem of a class of fully non-linear elliptic equations on compact Hermitian manifolds with real analytic Levi flat…

Analysis of PDEs · Mathematics 2022-03-08 Rirong Yuan

We introduce a novel class of semilinear nonlocal backward stochastic partial differential equations (BSPDE) on half-spaces driven by an infinite-dimensional c\`adl\`ag martingale. The equations exhibit a degeneracy and have no explicit…

Probability · Mathematics 2023-12-22 Ben Hambly , Philipp Jettkant

In this article we shall go over recent work in proving dispersive and Strichartz estimates for the Dirichlet-wave equation. We shall discuss applications to existence questions outside of obstacles and discuss open problems.

Analysis of PDEs · Mathematics 2007-05-23 Christopher D. Sogge

We continue the development, by reduction to a first order system for the conormal gradient, of $L^2$ \textit{a priori} estimates and solvability for boundary value problems of Dirichlet, regularity, Neumann type for divergence form second…

Classical Analysis and ODEs · Mathematics 2015-05-20 Pascal Auscher , Andreas Rosén

Stochastic gradient descent (SGD) provides a simple and efficient way to solve a broad range of machine learning problems. Here, we focus on distribution regression (DR), involving two stages of sampling: Firstly, we regress from…

Machine Learning · Statistics 2021-03-08 Nicole Mücke