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Related papers: Gradient estimates for nonlinear kinetic Fokker-Pl…

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We consider hypoelliptic equations of kinetic Fokker-Planck type, also known as Kolmogorov or ultraparabolic equations, with rough coefficients in the drift-diffusion operator. We give novel short quantitative proofs of the De Giorgi…

Analysis of PDEs · Mathematics 2022-07-13 Jessica Guerand , Clément Mouhot

In this manuscript, we investigate regularity estimates for a class of quasilinear elliptic equations in the non-divergence form that may exhibit degenerate behavior at critical points of their gradient. The prototype equation under…

Analysis of PDEs · Mathematics 2025-05-14 Junior da Silva Bessa , João Vitor da Silva

Recent years have seen a flurry of activities in designing provably efficient nonconvex procedures for solving statistical estimation problems. Due to the highly nonconvex nature of the empirical loss, state-of-the-art procedures often…

Machine Learning · Computer Science 2020-06-09 Cong Ma , Kaizheng Wang , Yuejie Chi , Yuxin Chen

We study the main properties of the solution of a Fokker-Planck equation characterized by a variable diffusion coefficient and a polynomial superlinear drift, modeling the formation of consensus in a large interacting system of individuals.…

Analysis of PDEs · Mathematics 2025-04-18 Giuseppe Toscani , Mattia Zanella

In this article we present new gradient estimates for positive solutions to a class of nonlinear elliptic equations involving the f-Laplacian on a smooth metric measure space. The gradient estimates of interest are of Souplet-Zhang and…

Analysis of PDEs · Mathematics 2023-06-16 Ali Taheri , Vahideh Vahidifar

Gradient regularization (GR) is a method that penalizes the gradient norm of the training loss during training. While some studies have reported that GR can improve generalization performance, little attention has been paid to it from the…

Machine Learning · Computer Science 2023-02-06 Ryo Karakida , Tomoumi Takase , Tomohiro Hayase , Kazuki Osawa

In this paper, we derive a priori estimates for the gradient and second order derivatives of solutions to a class of Hessian type fully nonlinear parabolic equations with the first initial-boundary value problem on Riemannian manifolds.…

Analysis of PDEs · Mathematics 2015-02-04 Ge-Jun Bao , Wei-Song Dong

We consider a nonlinear Fokker-Planck equation driven by a deterministic rough path which describes the conditional probability of a McKean-Vlasov diffusion with "common" noise. To study the equation we build a self-contained framework of…

Probability · Mathematics 2021-07-27 Michele Coghi , Torstein Nilssen

This paper focuses on finding an approximate solution of a kind of Fokker-Planck equation with time-dependent perturbations. A formulation of the approximate solution of the equation is constructed, and then the existence of the formulation…

Probability · Mathematics 2025-09-12 Yan Luo , Kaicheng Sheng

The aim of this thesis is to derive new gradient estimates for parabolic equations. The gradient estimates found are independent of the regularity of the initial data. This allows us to prove the existence of solutions to problems that have…

Analysis of PDEs · Mathematics 2007-05-23 Julie Clutterbuck

This article presents new parabolic and elliptic type gradient estimates for positive smooth solutions to a nonlinear parabolic equation involving the Witten Laplacian in the context of smooth metric measure spaces. The metric and potential…

Analysis of PDEs · Mathematics 2023-03-13 Ali Taheri , Vahideh Vahidifar

Starting from first principles, we formulate a theory of wave packet propagation in a nonlinear, disordered medium of any dimension, through the derivation of a Fokker-Planck transport equation. Our theory is based on a diagrammatic…

Disordered Systems and Neural Networks · Physics 2011-10-28 Nicolas Cherroret , Thomas Wellens

We present a framework, which, from the trajectories detailing the spatiotemporal dynamics of a population, simultaneously reconstructs a transport map as well as the Fokker-Planck equation governing the coarse-grained probability…

Dynamical Systems · Mathematics 2026-01-21 Saem Han , Krishna Garikipati

The aim of this paper is to establish an abstract theory based on the so-called fractional-maximal distribution functions (FMDs). From the rough ideas introduced in~\cite{AM2007}, we develop and prove some abstract results related to the…

Analysis of PDEs · Mathematics 2020-04-15 Thanh-Nhan Nguyen , Minh-Phuong Tran

This paper is devoted to a fundamental solution of a nonlinear kinetic equation involving a porous medium or fast diffusion operator acting on velocities. Such a nonlinearity has interesting scaling properties, which result in a…

Analysis of PDEs · Mathematics 2026-03-30 Giovanni Brigati , Guillaume Carlier , Jean Dolbeault

Estimating the score, i.e., the gradient of log density function, from a set of samples generated by an unknown distribution is a fundamental task in inference and learning of probabilistic models that involve flexible yet intractable…

Machine Learning · Statistics 2020-07-01 Yuhao Zhou , Jiaxin Shi , Jun Zhu

We establish the global existence of weak solutions to a nonlinear kinetic Fokker--Planck equation with degenerate diffusion, under either inflow or partial absorption-reflection boundary conditions. The novelty of our approach lies in…

Analysis of PDEs · Mathematics 2025-10-09 Young-Pil Choi , Sihyun Song

In this paper we study the {\it a priori} gradient estimates for admissible solutions to Neumann boundary value problem of fully nonlinear Hessian equations on Riemannian manifolds. We firstly derive an interior gradient estimates for…

Analysis of PDEs · Mathematics 2018-02-28 Weisong Dong

We prove global existence, uniqueness and regularity of the mild, Lp and classical solution of a non-linear Fokker-Planck equation arising in an adaptive importance sampling method for molecular dynamics calculations. The non- linear term…

Analysis of PDEs · Mathematics 2015-10-15 Houssam Alrachid , Tony Lelièvre , Raafat Talhouk

We study the gradient method under the assumption that an additively inexact gradient is available for, generally speaking, non-convex problems. The non-convexity of the objective function, as well as the use of an inexactness specified…

Optimization and Control · Mathematics 2022-12-13 Boris T. Polyak , Ilia A. Kuruzov , Fedor S. Stonyakin