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By using absolutely continuous lower bounds of the L\'evy measure, explicit gradient estimates are derived for the semigroup of the corresponding L\'evy process with a linear drift. A derivative formula is presented for the conditional…

Probability · Mathematics 2011-03-16 Feng-Yu Wang

In this work, we consider the bilevel optimization problem on Riemannian manifolds. We inspect the calculation of the hypergradient of such problems on general manifolds and thus enable the utilization of gradient-based algorithms to solve…

Optimization and Control · Mathematics 2024-02-09 Jiaxiang Li , Shiqian Ma

We prove new bounds on the control cost for the abstract heat equation, assuming a spectral inequality or uncertainty relation for spectral projectors. In particular, we specify quantitatively how upper bounds on the control cost depend on…

Analysis of PDEs · Mathematics 2020-10-01 Ivica Nakić , Matthias Täufer , Martin Tautenhahn , Ivan Veselic

We study heat kernel measures on sub-Riemannian infinite-dimensional Heisenberg-like Lie groups. In particular, we show that Cameron-Martin type quasi-invariance results hold in this subelliptic setting and give $L^p$-estimates for the…

Probability · Mathematics 2011-08-09 Fabrice Baudoin , Maria Gordina , Tai Melcher

In the paper we prove two inequalities in the setting of ${\sf RCD}(K,\infty)$ spaces using similar techniques. The first one is an indeterminacy estimate involving the $p$-Wasserstein distance between the positive part and the negative…

Differential Geometry · Mathematics 2022-02-08 Nicolò De Ponti , Sara Farinelli

We present a novel approach to approximate Gaussian and mixture-of-Gaussians filtering. Our method relies on a variational approximation via a gradient-flow representation. The gradient flow is derived from a Kullback--Leibler discrepancy…

Computation · Statistics 2023-06-21 Adrien Corenflos , Hany Abdulsamad

We introduce in this paper two time discretization schemes tailored for a range of Wasserstein gradient flows. These schemes are designed to preserve mass, positivity and to be uniquely solvable. In addition, they also ensure energy…

Numerical Analysis · Mathematics 2024-07-15 Shiheng Zhang , Jie Shen

A unified treatment is given of some results of H. Donnelly-P. Li and L. Schwartz concerning the behaviour of heat semigroups on open manifolds with given compactifications, on one hand, and the relationship with the behaviour at infinity…

Probability · Mathematics 2019-11-20 Xue-Mei Li

We introduce a new information-geometric structure associated with the dynamics on discrete objects such as graphs and hypergraphs. The presented setup consists of two dually flat structures built on the vertex and edge spaces,…

Information Theory · Computer Science 2023-08-08 Tetsuya J. Kobayashi , Dimitri Loutchko , Atsushi Kamimura , Shuhei A. Horiguchi , Yuki Sughiyama

In the first part of this paper, we prove local interior and boundary gradient estimates for p-harmonic functions on general Riemannian manifolds. With these estimates, following the strategy in recent work of R. Moser, we prove an…

Analysis of PDEs · Mathematics 2007-11-15 Brett Kotschwar , Lei Ni

Let (P(t)) be the Ornstein-Uhlenbeck semigroup associated with the stochastic Cauchy problem dU(t) = AU(t)dt + dW_H(t), where A is the generator of a C_0-semigroup (S(t)) on a Banach space E, H is a Hilbert subspace of E, and (W_H(t)) is an…

Functional Analysis · Mathematics 2011-02-07 Jan Maas , Jan van Neerven

This paper addresses the problems of spline interpolation on smooth Riemannian manifolds, with or without the inclusion of least-squares fitting. Our unified approach utilizes gradient flows for successively connected curves or networks,…

Optimization and Control · Mathematics 2025-10-29 Chun-Chi Lin , Dung The Tran

We study the structure of the support of a doubling measure by analyzing its self-similarity properties, which we estimate using a variant of the $L^1$ Wasserstein distance. We show that measure satisfying certain self-similarity conditions…

Metric Geometry · Mathematics 2014-11-11 Jonas Azzam , Guy David , Tatiana Toro

In this paper we study a gradient flow approach to the problem of quantization of measures in one dimension. By embedding our problem in $L^2$, we find a continuous version of it that corresponds to the limit as the number of particles…

Analysis of PDEs · Mathematics 2016-01-26 Emanuele Caglioti , François Golse , Mikaela Iacobelli

In recent work [1] we uncovered intriguing connections between Otto's characterisation of diffusion as entropic gradient flow [16] on one hand and large-deviation principles describing the microscopic picture (Brownian motion) on the other.…

Analysis of PDEs · Mathematics 2014-03-05 Stefan Adams , Nicolas Dirr , Mark A. Peletier , Johannes Zimmer

The gradient flow of the Canham-Helfrich functional is tackled via the Generalized Minimizing Movements approach. We prove the existence of solutions in Wasserstein spaces of varifolds, as well as upper and lower diameter bounds. In the…

Analysis of PDEs · Mathematics 2022-07-08 Katharina Brazda , Martin Kružík , Ulisse Stefanelli

We find examples of duality among quantum theories that are related to arithmetic functions by identifying distinct Hamiltonians that have identical partition functions at suitably related coupling constants or temperatures. We are led to…

High Energy Physics - Theory · Physics 2010-12-17 Donald Spector

We derive a sharp, localized version of elliptic type gradient estimates for positive solutions (bounded or not) to the heat equation. These estimates are akin to the Cheng-Yau estimate for the Laplace equation and Hamilton's estimate for…

Differential Geometry · Mathematics 2007-05-23 Philippe Souplet , Qi S. Zhang

We study policy gradient methods for continuous-action, entropy-regularized reinforcement learning through the lens of Wasserstein geometry. Starting from a Wasserstein proximal update, we derive Wasserstein Proximal Policy Gradient (WPPG)…

Machine Learning · Computer Science 2026-03-04 Zhaoyu Zhu , Shuhan Zhang , Rui Gao , Shuang Li

Over the past fifteen years, the theory of Wasserstein gradient flows of convex (or, more generally, semiconvex) energies has led to advances in several areas of partial differential equations and analysis. In this work, we extend the…

Analysis of PDEs · Mathematics 2017-05-04 Katy Craig