Generalized Belief Propagation for Estimating the Partition Function of the 2D Ising Model

Chan, Chun Lam and Siavoshani, Mahdi Jafari and Jaggi, Sidharth and Kashyap, Navin and Vontobel, Pascal O (2015) Generalized Belief Propagation for Estimating the Partition Function of the 2D Ising Model. In: IEEE International Symposium on Information Theory (ISIT), JUN 14-19, 2015, Hong Kong, PEOPLES R CHINA, pp. 2261-2265.

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Abstract

Recent empirical results have demonstrated that generalized belief propagation (GBP) can be used to closely estimate the capacity of certain 2D runlength-limited constraints. We provide a partial analytical validation of these observations by showing that GBP yields a lower bound on the partition function of 2D Ising models with restricted grid size. While previous papers have proved that belief propagation (BP) can be used to obtain a lower bound on the partition function of 2D Ising models, this paper is the first work that analyzes GBP-based partition function approximations of 2D Ising models.

Item Type:	Conference Proceedings
Series.:	IEEE International Symposium on Information Theory
Additional Information:	Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	07 Dec 2016 05:47
Last Modified:	07 Dec 2016 05:47
URI:	http://eprints.iisc.ac.in/id/eprint/55514

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