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Related papers: Bethe-Peierls approximation and the inverse Ising …

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This work explores the possibilities of the Gibbs-Bogoliubov-Feynman variational method, aiming at finding room for designing various drawing schemes. For example, mean-field approximation can be viewed as a result of using site-independent…

Statistical Mechanics · Physics 2025-09-08 Oliwier Urbański

We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for…

Disordered Systems and Neural Networks · Physics 2013-05-30 Erik Aurell , Magnus Ekeberg

The adaptive Thouless-Anderson-Palmer equation is derived for inverse Ising problems in the presence of quenched random fields. We test the proposed scheme on Sherrington-Kirkpatrick, Hopfield, and random orthogonal models and find that the…

Disordered Systems and Neural Networks · Physics 2013-06-28 Haiping Huang , Yoshiyuki Kabashima

We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the…

High Energy Physics - Lattice · Physics 2009-06-09 Cayetano Di Bartolo , Lorenzo Leal

Network structures are reconstructed from dynamical data by respectively naive mean field (nMF) and Thouless-Anderson-Palmer (TAP) approximations. For TAP approximation, we use two methods to reconstruct the network: a) iteration method; b)…

Computation · Statistics 2015-05-20 Hong-Li Zeng , Erik Aurell , Mikko Alava , Hamed Mahmoudi

Consider a collection of random variables attached to the vertices of a graph. The reconstruction problem requires to estimate one of them given `far away' observations. Several theoretical results (and simple algorithms) are available when…

Probability · Mathematics 2007-09-10 Antoine Gerschenfeld , Andrea Montanari

Variational inference in probabilistic graphical models aims to approximate fundamental quantities such as marginal distributions and the partition function. Popular approaches are the Bethe approximation, tree-reweighted, and other types…

Machine Learning · Statistics 2025-02-06 Harald Leisenberger , Franz Pernkopf

We consider ferromagnetic Ising models on graphs that converge locally to trees. Examples include random regular graphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the "cavity" prediction for…

Probability · Mathematics 2016-09-08 Amir Dembo , Andrea Montanari

The mean field approximation to the Ising model is a canonical variational tool that is used for analysis and inference in Ising models. We provide a simple and optimal bound for the KL error of the mean field approximation for Ising models…

Machine Learning · Computer Science 2018-02-22 Vishesh Jain , Frederic Koehler , Elchanan Mossel

Tree reconstruction methods are often judged by their accuracy, measured by how close they get to the true tree. Yet most reconstruction methods like ML do not explicitly maximize this accuracy. To address this problem, we propose a…

Populations and Evolution · Quantitative Biology 2009-11-22 Peter Huggins , Wenbin Li , David Haws , Thomas Friedrich , Jinze Liu , Ruriko Yoshida

Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.…

Quantitative Methods · Quantitative Biology 2007-12-18 Tamara Broderick , Miroslav Dudik , Gasper Tkacik , Robert E. Schapire , William Bialek

The main contribution of the current study is two-fold. First, we investigate the energy landscape of the Ising and Potts models on finite two-dimensional lattices without external fields in the low temperature regime. The complete analysis…

Probability · Mathematics 2023-01-05 Seonwoo Kim , Insuk Seo

We develop a transfer matrix method to compute exactly the spin-spin correlation functions of Bethe lattice spin models in the external magnetic field h and for any temperature T. We first compute the correlation function for the most…

Statistical Mechanics · Physics 2009-10-31 Chin-Kun Hu , N. Sh. Izmailian

We calculate equilibrium solutions for Ising spin models on `small world' lattices, which are constructed by super-imposing random and sparse Poissonian graphs with finite average connectivity c onto a one-dimensional ring. The nearest…

Disordered Systems and Neural Networks · Physics 2009-11-10 T. Nikoletopoulos , A. C. C. Coolen , I. Perez-Castillo , N. S. Skantzos , J. P. L. Hatchett , B. Wemmenhove

We study systems without quenched disorder with a complex landscape, and we use replica symmetry theory to describe them. We discuss the Golay-Bernasconi-Derrida approximation of the low autocorrelation model, and we reconstruct it by using…

High Energy Physics - Theory · Physics 2009-10-28 E. Marinari , G. Parisi , F. Ritort

The classical transverse field Ising spin- glass model with short-range interactions is investigated beyond the mean- field approximation for a real d- dimensional lattice. We use an appropriate nontrivial modification of the Bethe- Peierls…

Disordered Systems and Neural Networks · Physics 2009-10-31 K Walasek , K Lukierska- Walasek , L De Cesare , I Rabuffo

We present a systematic small-correlation expansion to solve the inverse Ising problem: find a set of couplings and fields corresponding to a given set of correlations and magnetizations. Couplings are calculated up to the third order in…

Disordered Systems and Neural Networks · Physics 2009-01-07 Vitor Sessak , Rémi Monasson

Reconstruction of structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine…

Statistical Mechanics · Physics 2017-12-27 Andrey Y. Lokhov , Marc Vuffray , Sidhant Misra , Michael Chertkov

A scheme to provide various mean-field-type approximation algorithms is presented by employing the Bethe free energy formalism to a family of replicated systems in conjunction with analytical continuation with respect to the number of…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yoshiyuki Kabashima

Infinite-range spin-glass models with Levy-distributed interactions show a freezing transition similar to disordered spin systems on finite connectivity random graphs. It is shown that despite diverging moments of the local field…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Engel