Network inference using asynchronously updated kinetic Ising Model

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Zeng, Hong-Li Aurell, Erik Alava, Mikko Mahmoudi, Hamed 2017-10-15T20:55:25Z 2017-10-15T20:55:25Z 2011
dc.identifier.citation Zeng , H-L , Aurell , E , Alava , M & Mahmoudi , H 2011 , ' Network inference using asynchronously updated kinetic Ising Model ' PHYSICAL REVIEW E , vol 83 , no. 4 , 041135 , pp. 1-6 . DOI: 10.1103/PhysRevE.83.041135 en
dc.identifier.issn 1539-3755
dc.identifier.issn 1550-2376
dc.identifier.other PURE UUID: c2f5dd74-d96d-47ca-8db0-9c7aa7fb87b8
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE LINK:
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dc.description.abstract Network structures are reconstructed from dynamical data by respectively naive mean field (nMF) and Thouless-Anderson-Palmer (TAP) approximations. TAP approximation adds simple corrections to the nMF approximation, taking into account the effect of the focused spin on itself via its influence on other neighboring spins. For TAP approximation, we use two methods to reconstruct the network: (a) iterative method; (b) casting the inference formula to a set of cubic equations and solving it directly. We investigate inference of the asymmetric Sherrington-Kirkpatrick (aS-K) model using asynchronous update. The solutions of the set of cubic equations depend on temperature T in the aS-K model, and a critical temperature Tc≈2.1 is found. The two methods for TAP approximation produce the same results when the iterative method is convergent. Compared to nMF, TAP is somewhat better at low temperatures, but approaches the same performance as temperature increases. Both nMF and TAP approximation reconstruct better for longer data length L, but for the degree of improvement, TAP performs better than nMF. en
dc.format.extent 1-6
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries PHYSICAL REVIEW E en
dc.relation.ispartofseries Volume 83, issue 4 en
dc.rights openAccess en
dc.subject.other 114 Physical sciences en
dc.subject.other 221 Nanotechnology en
dc.subject.other 214 Mechanical engineering en
dc.subject.other 218 Environmental engineering en
dc.title Network inference using asynchronously updated kinetic Ising Model en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Applied Physics
dc.contributor.department School services, SCI
dc.subject.keyword 114 Physical sciences
dc.subject.keyword 221 Nanotechnology
dc.subject.keyword 214 Mechanical engineering
dc.subject.keyword 218 Environmental engineering
dc.identifier.urn URN:NBN:fi:aalto-201710157154
dc.identifier.doi 10.1103/PhysRevE.83.041135
dc.type.version publishedVersion

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