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Gaussian mixture models (GMMs) are ubiquitous in statistical learning, particularly for unsupervised problems. While full GMMs suffer from the overparameterization of their covariance matrices in high-dimensional spaces, spherical GMMs…

Machine Learning · Statistics 2025-11-10 Tom Szwagier , Pierre-Alexandre Mattei , Charles Bouveyron , Xavier Pennec

In this paper we discuss about the validity of the Shannon entropy functional in connection with the correct Gibbs-Hertz probability distribution function. We show that there is no contradiction in using the Shannon-Gibbs functional and…

Classical Physics · Physics 2015-03-11 Alessio Gagliardi , Alessandro Pecchia

In this paper, we prove the concavity of the Shannon entropy power for the heat equation associated with the Laplacian or the Witten Laplacian on complete Riemannian manifolds with suitable curvature-dimension condition and on compact super…

Differential Geometry · Mathematics 2020-01-03 S. Li , X. -D. Li

In recent papers, several authors have claimed that a definition of the thermodynamic entropy in terms of the logarithm of a volume in phase space, originally suggested by Gibbs, is the only valid definition. Arguing from the Gibbs entropy,…

Statistical Mechanics · Physics 2015-08-26 Robert H. Swendsen , Jian-Sheng Wang

The concept of Entropy plays a key role in Information Theory, Statistics, and Machine Learning.This paper introduces a new entropy measure, called the t-entropy, which exploits the concavity of the inverse-tan function. We analytically…

Information Theory · Computer Science 2021-05-06 Saptarshi Chakraborty , Debolina Paul , Swagatam Das

In this work we prove sufficient conditions for the Glauber dynamics corresponding to a sequence of (non-product) measures on finite product spaces to be rapidly mixing, i.e. that the mixing time with respect to the total variation distance…

Probability · Mathematics 2019-02-27 Arthur Sinulis

Consider tossing a collection of coins, each fair or biased towards heads, and take the distribution of the total number of heads that result. It is natural to conjecture that this distribution should be 'more random' when each coin is…

Probability · Mathematics 2019-11-20 Erwan Hillion , Oliver Johnson

An improved volume-weighted probability measure for eternal inflation is proposed. For the models studied in this paper it leads to simple and intuitively expected gauge-invariant results.

High Energy Physics - Theory · Physics 2009-11-13 Andrei Linde

We prove the correspondence between the solutions of the sub-elliptic heat equation in a Carnot group $\mathbb{G}$ and the gradient flows of the relative entropy functional in the Wasserstein space of probability measures on $\mathbb{G}$.…

Differential Geometry · Mathematics 2023-09-07 Luigi Ambrosio , Giorgio Stefani

We present an exact Monte Carlo algorithm designed to sample theories where the energy is a sum of many couplings of decreasing strength. Our algorithm, simplified from that of L. Lin et al. hep-lat/9905033, avoids the computation of almost…

High Energy Physics - Lattice · Physics 2009-10-31 T. Bakeyev , Ph. de Forcrand

We present precise moderate deviation probabilities, in both quenched and annealed settings, for a recurrent diffusion process with a Brownian potential. Our method relies on fine tools in stochastic calculus, including Kotani's lemma and…

Probability · Mathematics 2007-05-23 Yueyun Hu , Zhan Shi

We formulate a mixed-state analog of the NLTS conjecture [FH14] by asking whether there exist topologically-ordered systems for which the thermal Gibbs state for constant temperature is globally-entangled in the sense that it cannot even be…

Quantum Physics · Physics 2020-09-09 Lior Eldar

Multimodal structures in the sampling density (e.g. two competing phases) can be a serious problem for traditional Markov Chain Monte Carlo (MCMC), because correct sampling of the different structures can only be guaranteed for infinite…

Data Analysis, Statistics and Probability · Physics 2009-11-11 M. Daghofer , M. Konegger , H. G. Evertz , W. von der Linden

Generalized empirical likelihood and generalized method of moments are well spread methods of resolution of inverse problems in econometrics. Each method defines a specific semiparametric model for which it is possible to calculate…

Statistics Theory · Mathematics 2010-11-24 Paul Rochet

In this paper we prove uniform regularity estimates for the normalized Gauss curvature flow in higher dimensions. The convergence of solutions in $C^\infty$-topology to a smooth strictly convex soliton as $t$ approaches to infinity is…

Differential Geometry · Mathematics 2013-06-05 Pengfei Guan , Lei Ni

We consider an isomorphism invariant for measure-preserving systems - types of generalized entropy convergence rates. We show the connections of this invariant with the types of Shannon entropy convergence rates. In the case when they…

Dynamical Systems · Mathematics 2013-09-25 Fryderyk Falniowski

We prove that a self similar measure is absolutely continuous providing that it satisfies a condition depending on its Garsia entropy, contraction ratio, and the separation between different points in approximations of the self similar…

Dynamical Systems · Mathematics 2023-02-07 Samuel Kittle

We provide a new proof of the abstract random tensor estimate. This estimate was initially proven by Deng, Nahmod, and Yue (2022) using the moment method. The key new tool in our proof is the direct use of the non-commutative Khintchine…

Probability · Mathematics 2025-12-04 Claire Kaneshiro

We show that an arbitrary Anosov Gaussian thermostat close to equilibrium has positive entropy poduction unless the external field $E$ has a global potential. The configuration space is allowed to have any dimension and magnetic forces are…

Dynamical Systems · Mathematics 2009-11-11 Nurlan S. Dairbekov , Gabriel P. Paternain

We show that a certain entropy-like function is convex, under an optimal transport problem that is adapted to Ricci flow. We use this to reprove the monotonicity of Perelman's reduced volume.

Differential Geometry · Mathematics 2009-01-09 John Lott
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