Universität zu Köln

Dettmer, Simon L., Nguyen, H. Chau and Berg, Johannes (2016). Network inference in the nonequilibrium steady state. Phys. Rev. E, 94 (5). COLLEGE PK: AMER PHYSICAL SOC. ISSN 2470-0053

Full text not available from this repository.

Abstract

Nonequilibrium systems lack an explicit characterization of their steady state like the Boltzmann distribution for equilibrium systems. This has drastic consequences for the inference of the parameters of a model when its dynamics lacks detailed balance. Such nonequilibrium systems occur naturally in applications like neural networks and gene regulatory networks. Here, we focus on the paradigmatic asymmetric Ising model and show that we can learn its parameters from independent samples of the nonequilibrium steady state. We present both an exact inference algorithm and a computationally more efficient, approximate algorithm for weak interactions based on a systematic expansion around mean-field theory. Obtaining expressions for magnetizations and two- and three-point spin correlations, we establish that these observables are sufficient to infer the model parameters. Further, we discuss the symmetries characterizing the different orders of the expansion around the mean field and show how different types of dynamics can be distinguished on the basis of samples from the nonequilibrium steady state.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Dettmer, Simon L. UNSPECIFIED UNSPECIFIED UNSPECIFIED Nguyen, H. Chau UNSPECIFIED UNSPECIFIED UNSPECIFIED Berg, Johannes UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-255792
DOI:	10.1103/PhysRevE.94.052116
Journal or Publication Title:	Phys. Rev. E
Volume:	94
Number:	5
Date:	2016
Publisher:	AMER PHYSICAL SOC
Place of Publication:	COLLEGE PK
ISSN:	2470-0053
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Physics > Institut für Biologische Physik
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language MEAN-FIELD THEORY; BOLTZMANN MACHINES; ISING-MODEL; SPIN-GLASS; ALGORITHM Multiple languages Physics, Fluids & Plasmas; Physics, Mathematical Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/25579