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Given a set of several inputs into a system (e.g., independent variables characterizing stimuli) and a set of several stochastically non-independent outputs (e.g., random variables describing different aspects of responses), how can one…

Data Analysis, Statistics and Probability · Physics 2012-09-04 Ehtibar N. Dzhafarov , Janne V. Kujala

We present a general analytic method to compute the number of metastable configurations as a function of the energy for a system of interacting Ising spins on the Bethe lattice. Our approach is based on the cavity method. We apply it to the…

Statistical Mechanics · Physics 2009-11-07 A. Pagnani , G. Parisi , M. Ratieville

We first describe a general class of optimization problems that describe many natural, economic, and statistical phenomena. After noting the existence of a conserved quantity in a transformed coordinate system, we outline several instances…

Optimization and Control · Mathematics 2018-04-03 David Rushing Dewhurst

Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the output of numerical methods. The use of these methods is usually motivated by the fact that they can represent our uncertainty due to…

Computation · Statistics 2018-08-01 Xiaoyue Xi , François-Xavier Briol , Mark Girolami

Disordered and frustrated graphical systems are ubiquitous in physics, biology, and information science. For models on complete graphs or random graphs, deep understanding has been achieved through the mean-field replica and cavity methods.…

Statistical Mechanics · Physics 2012-04-10 Haijun Zhou , Chuang Wang , Jing-Qing Xiao , Zedong Bi

We define one-dimensional particles with generalized exchange statistics. The exact solution of a Hubbard-type Hamiltonian constructed with such particles is achieved using the Coordinate Bethe Ansatz. The chosen deformation of the…

Strongly Correlated Electrons · Physics 2007-05-23 A. Osterloh , L. Amico , U. Eckern

We introduce a version of the cavity method for diluted mean-field spin models that allows the computation of thermodynamic quantities similar to the Franz-Parisi quenched potential in sparse random graph models. This method is developed in…

Disordered Systems and Neural Networks · Physics 2015-05-13 Federico Ricci-Tersenghi , Guilhem Semerjian

The partition function of the random energy model at inverse temperature $\beta$ is a sum of random exponentials $Z_N(\beta)=\sum_{k=1}^N \exp(\beta \sqrt{n} X_k)$, where $X_1,X_2,...$ are independent real standard normal random variables…

Probability · Mathematics 2014-02-11 Zakhar Kabluchko , Anton Klimovsky

In this note we explain the use of the cavity method directly at zero temperature, in the case of the spin glass on a Bethe lattice. The computation is done explicitly in the formalism equivalent to 'one step replica symmetry breaking'; we…

Disordered Systems and Neural Networks · Physics 2007-05-23 Marc Mezard , Giorgio Parisi

Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the…

Machine Learning · Computer Science 2019-07-09 Frank Nussbaum , Joachim Giesen

We study the problem of approximately counting matchings in hypergraphs of bounded maximum degree and maximum size of hyperedges. With an activity parameter $\lambda$, each matching $M$ is assigned a weight $\lambda^{|M|}$. The counting…

Data Structures and Algorithms · Computer Science 2017-01-09 Renjie Song , Yitong Yin , Jinman Zhao

Employing heuristic susceptibility equations in conjunction with the well-known critical exponents, the magnetization and partition function for two-dimensional nearest neighbour Ising models are formulated in terms of the Gauss…

Statistical Mechanics · Physics 2019-12-18 M. V. Sangaranarayanan

Gibbs-type exchangeable random partitions, which is a class of multiplicative measures on the set of positive integer partitions, appear in various contexts, including Bayesian statistics, random combinatorial structures, and stochastic…

Statistics Theory · Mathematics 2017-06-14 Shuhei Mano

We propose a new approximate method for counting the number of the solutions for constraint satisfaction problem (CSP). The method derives from the partition function based on introducing the free energy and capturing the relationship of…

Artificial Intelligence · Computer Science 2013-09-12 Junping Zhou , Weihua Su , Minghao Yin

We study computational aspects of repulsive Gibbs point processes, which are probabilistic models of interacting particles in a finite-volume region of space. We introduce an approach for reducing a Gibbs point process to the hard-core…

Data Structures and Algorithms · Computer Science 2023-12-15 Tobias Friedrich , Andreas Göbel , Maximilian Katzmann , Martin Krejca , Marcus Pappik

In its continuous version, the entropy functional measuring the information content of a given probability density may be plagued by a "measure" problem that results from improper weighting of phase space. This issue is addressed…

Statistical Mechanics · Physics 2011-06-08 P. Maynar , E. Trizac

We use the cavity method to study parallel dynamics of disordered Ising models on a graph. In particular, we derive a set of recursive equations in single site probabilities of paths propagating along the edges of the graph. These equations…

Disordered Systems and Neural Networks · Physics 2025-04-23 I. Neri , D. Bollé

We study the problem of approximating the partition function of the ferromagnetic Ising model in graphs and hypergraphs. Our first result is a deterministic approximation scheme (an FPTAS) for the partition function in bounded degree graphs…

Data Structures and Algorithms · Computer Science 2018-12-26 Jingcheng Liu , Alistair Sinclair , Piyush Srivastava

We consider the problem of approximating partition functions for Ising models. We make use of recent tools in combinatorial optimization: the Sherali-Adams and Lasserre convex programming hierarchies, in combination with variational methods…

Machine Learning · Computer Science 2016-07-13 Andrej Risteski

We present an efficient sampling method for computing a partition function and accelerating configuration sampling. The method performs a random walk in the $\lambda$ space, with $\lambda$ being any thermodynamic variable that characterizes…

Computational Physics · Physics 2010-03-02 Cheng Zhang , Jianpeng Ma