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We take another look at the general problem of selecting a preferred probability measure among those that comply with some given constraints. The dominant role that entropy maximization has obtained in this context is questioned by arguing…

Artificial Intelligence · Computer Science 2013-02-01 Manfred Jaeger

A modification of Coulomb's law of friction uses a variable coefficient of friction that depends on a power law in the energy of mechanical oscillation. Through the use of three different exponents: 0, 1/2 and 1; all commonly encountered…

Classical Physics · Physics 2007-05-23 Randall D. Peters

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a {\em stochastic maximal inequality} derived by using the formula for…

Probability · Mathematics 2017-08-16 Yoichi Nishiyama

Motivated by compartmental analysis in engineering and biophysical systems, we present a variational framework for the nonequilibrium thermodynamics of systems involving both distributed and discrete (finite dimensional) subsystems by…

Statistical Mechanics · Physics 2022-04-07 François Gay-Balmaz , Hiroaki Yoshimura

We study the following question: given a massive Markov random field on $n$ nodes, can a small sample from it provide a rough approximation to the free energy $\mathcal{F}_n = \log{Z_n}$? Results in graph limit literature by Borgs, Chayes,…

Machine Learning · Computer Science 2018-02-27 Vishesh Jain , Frederic Koehler , Elchanan Mossel

Approximating marginals of a graphical model is one of the fundamental problems in the theory of networks. In a recent paper a method was shown to construct a variational free energy such that the linear response estimates, and maximum…

Disordered Systems and Neural Networks · Physics 2014-05-01 Jack Raymond , Federico Ricci-Tersenghi

A strong invariance principle is established for random fields which satisfy dependence conditions more general than positive or negative association. We use the approach of Cs\"{o}rg\H{o} and R\'{e}v\'{e}sz applied recently by Balan to…

Probability · Mathematics 2007-05-23 Alexander Bulinski , Alexey Shashkin

We introduce two new particle-based algorithms for learning latent variable models via marginal maximum likelihood estimation, including one which is entirely tuning-free. Our methods are based on the perspective of marginal maximum…

Machine Learning · Statistics 2024-03-04 Louis Sharrock , Daniel Dodd , Christopher Nemeth

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower…

Machine Learning · Statistics 2019-06-12 Nikolaos Gianniotis , Christoph Schnörr , Christian Molkenthin , Sanjay Singh Bora

Post-selected weak measurement has been widely used in experiments to observe weak effects in various physical systems. However, it is still unclear how large the amplification ability of a weak measurement can be and what determines the…

Quantum Physics · Physics 2014-07-17 Shengshi Pang , Todd A. Brun , Shengjun Wu , Zeng-Bing Chen

Modeling microstructure evolution in electrochemical systems is vital for understanding the mechanism of various electrochemical processes. In this work, we propose a general phase field framework that is fully variational and thus…

Materials Science · Physics 2023-12-12 Jin Zhang , Alexander F. Chadwick , Peter W. Voorhees

Variational formalism in the extended phase space for fields is applied to gravity. It is shown that the requirement of invariance under arbitrary local inertial frames implies a coupling of torsion to a 3-form of matter fields on the one…

General Relativity and Quantum Cosmology · Physics 2012-04-04 Pankaj Sharan

Vibrating systems can respond to an infinite number of initial conditions and the overall dynamics of the system can be strongly affected by them. Therefore, it is of practical importance to have methods by which we can determine the…

Classical Physics · Physics 2025-04-08 Karlo Lelas

We present a variational inference (VI) framework that unifies and leverages sequential Monte-Carlo (particle filtering) with \emph{approximate} rejection sampling to construct a flexible family of variational distributions. Furthermore, we…

Machine Learning · Computer Science 2021-03-30 Rahul Sharma , Soumya Banerjee , Dootika Vats , Piyush Rai

The review paper presents generalization of d'Alembert's variational principle: the dynamics of a quantum system for an external observer is defined by the exact equilibrium of all acting in the system forces, including the random quantum…

High Energy Physics - Theory · Physics 2015-05-20 J. Manjavidze

In this paper we extend, for the first time, part of the Weierstrass extremal field theory in the Calculus of Variations to a nonlocal framework. Our model case is the energy functional for the fractional Laplacian (the Gagliardo-Sobolev…

Analysis of PDEs · Mathematics 2022-12-02 Xavier Cabre , Iñigo U. Erneta , Juan-Carlos Felipe-Navarro

In this paper we survey some recent results on the central limit theorem and its weak invariance principle for stationary sequences. We also describe several maximal inequalities that are the main tool for obtaining the invariance…

Probability · Mathematics 2016-08-16 Florence Merlevède , Magda Peligrad , Sergey Utev

Following Feynman's treatment of the non-relativistic polaron problem, similar techniques are used to study relativistic field theories: after integrating out the bosonic degrees of freedom the resulting effective action is formulated in…

High Energy Physics - Theory · Physics 2007-05-23 R. Rosenfelder , C. Alexandrou , A. W. Schreiber

Motivated by the analysis of thin structures, we study the variational dimension reduction of hyperelastic energies involving nonlocal gradients to an effective membrane model. When rescaling the thin domain, isotropic interaction ranges…

Analysis of PDEs · Mathematics 2026-02-24 Dominik Engl , Anastasia Molchanova , Hidde Schönberger

We present a lower bound for the free energy of a quantum many-body system at finite temperature. This lower bound is expressed as a convex optimization problem with linear constraints, and is derived using strong subadditivity of von…

Quantum Physics · Physics 2015-05-20 David Poulin , Matthew B. Hastings