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In the context of kernel methods, the similarity between data points is encoded by the kernel function which is often defined thanks to the Euclidean distance, a common example being the squared exponential kernel. Recently, other distances…

Machine Learning · Computer Science 2020-02-06 Henri De Plaen , Michaël Fanuel , Johan A. K. Suykens

We prove a new version of Egorov's theorem formulated in the Schr\"{o}dinger picture of quantum mechanics, using the $p$-Wasserstein metric applied to the Husimi functions of quantum states. The special case $p=1$ corresponds to a…

Quantum Physics · Physics 2025-09-10 Jordan Cotler , Felipe Hernández

We extend a class of recently derived thermodynamic uncertainty relations to vector-valued observables. In contrast to the scalar-valued observables examined previously, this multidimensional thermodynamic uncertainty relation provides a…

Statistical Mechanics · Physics 2019-10-22 Andreas Dechant

This work is devoted to the Lipschitz contraction and the long time behavior of certain Markov processes. These processes diffuse and jump. They can represent some natural phenomena like size of cell or data transmission over the Internet.…

Probability · Mathematics 2012-10-12 Bertrand Cloez

We consider Monge-Kantorovich optimal transport problems on $\mathbb{R}^d$, $d\ge 1$, with a convex cost function given by the cumulant generating function of a probability measure. Examples include the Wasserstein-2 transport whose cost…

Probability · Mathematics 2017-08-29 Soumik Pal

We study the Classical Probability analogue of the dilations of a quantum dynamical semigroup defined in Quantum Probability via quantum stochastic differential equations. Given a homogeneous Markov chain in continuous time in a finite…

Probability · Mathematics 2008-09-02 M. Gregoratti

It is well known that nonlinear diffusion equations can be interpreted as a gradient flow in the space of probability measures equipped with the Euclidean Wasserstein distance. Under suitable convexity conditions on the nonlinearity, due to…

Analysis of PDEs · Mathematics 2014-02-13 François Bolley , José A. Carrillo

We consider the Cauchy problem for the heat diffusion equation in the whole Euclidean space consisting of two media locally with different constant conductivities, where initially one medium has temperature 0 and the other has temperature…

Analysis of PDEs · Mathematics 2025-02-26 Shigeru Sakaguchi

We extend the dimension free Talagrand inequalities for convex distance \cite{talagrand:1995} using an extension of Marton's weak transport \cite{marton:1996a} to other metrics than the Hamming distance. We study the dual form of these weak…

Probability · Mathematics 2014-03-06 Olivier Wintenberger

We introduce a modified Benamou-Brenier type approach leading to a Wasserstein type distance that allows global invariance, specifically, isometries, and we show that the problem can be summarized to orthogonal transformations. This…

Machine Learning · Statistics 2025-03-24 Kevine Meugang Toukam

During the last decade Optimal Transport had a relevant role in the study of geometry of singular spaces that culminated with the Lott-Sturm-Villani theory. The latter is built on the characterisation of Ricci curvature lower bounds in…

Metric Geometry · Mathematics 2020-05-04 Fabio Cavalletti , Nicola Gigli , Flavia Santarcangelo

We propose a class of semimetrics for preference relations any one of which is an alternative to the classical Kemeny-Snell-Bogart metric. (We take a fairly general viewpoint about what constitutes a preference relation, allowing for any…

Combinatorics · Mathematics 2022-03-10 Hiroki Nishimura , Efe A. Ok

Various properties of isoperimetric, functional, Transport-Entropy and concentration inequalities are studied on a Riemannian manifold equipped with a measure, whose generalized Ricci curvature is bounded from below. First, stability of…

Functional Analysis · Mathematics 2010-11-11 Emanuel Milman

An analogue of the quadratic Wasserstein (or Monge-Kantorovich) distance between Borel probability measures on $\mathbf{R}^d$ has been defined in [F. Golse, C. Mouhot, T. Paul: Commun. Math. Phys. 343 (2015), 165-205] for density operators…

Mathematical Physics · Physics 2021-02-10 Emanuele Caglioti , François Golse , Thierry Paul

We derive a class of divergences measuring the difference between probability density functions on the one-dimensional sample space. This divergence is a one-parameter variation of the Itakura--Saito divergence between quantile density…

Information Theory · Computer Science 2026-02-20 Wuchen Li

Motivated by the Asymptotic Equipartition Property and its recently discovered role in the cutoff phenomenon, we initiate the systematic study of varentropy on discrete groups. Our main result is an approximate tensorization inequality…

Probability · Mathematics 2024-09-26 Jonathan Hermon , Xiangying Huang , Francesco Pedrotti , Justin Salez

We propose a new generalization to quantum states of the Wasserstein distance, which is a fundamental distance between probability distributions given by the minimization of a transport cost. Our proposal is the first where the transport…

Mathematical Physics · Physics 2021-09-21 Giacomo De Palma , Dario Trevisan

We study the Classical Probability analogue of the dilations of a quantum dynamical semigroup in Quantum Probability. Given a (not necessarily homogeneous) Markov chain in discrete time in a finite state space E, we introduce a second…

Probability · Mathematics 2007-05-23 M. Gregoratti

We consider an ordinary differential equation with a unique hyperbolic attractor at the origin, to which we add a small random perturbation. It is known that under general conditions, the solution of this stochastic differential equation…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Milton Jara

The time-evolution of a moderately dense gas in a vacuum is described in classical mechanics by a particle density function obtained from the Enskog equation. Based on a McKean-Vlasov stochastic equation with jumps, the associated…

Analysis of PDEs · Mathematics 2020-04-16 Martin Friesen , Barbara Rüdiger , Padmanabhan Sundar
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