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NIPS
2008
13 years 9 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
NIPS
2000
13 years 9 months ago
Generalized Belief Propagation
In an important recent paper, Yedidia, Freeman, and Weiss [11] showed that there is a close connection between the belief propagation algorithm for probabilistic inference and the...
Jonathan S. Yedidia, William T. Freeman, Yair Weis...
ASUNAM
2010
IEEE
13 years 8 months ago
Product Adoption Networks and Their Growth in a Large Mobile Phone Network
—To understand the diffusive spreading of a product in a telecom network, whether the product is a service, handset, or subscription, it can be very useful to study the structure...
Pal Roe Sundsoy, Johannes Bjelland, Geoffrey Canri...
BMCBI
2010
86views more  BMCBI 2010»
13 years 8 months ago
Protein binding hot spots and the residue-residue pairing preference: a water exclusion perspective
Background: A protein binding hot spot is a small cluster of residues tightly packed at the center of the interface between two interacting proteins. Though a hot spot constitutes...
Qian Liu, Jinyan Li
BMCBI
2007
160views more  BMCBI 2007»
13 years 8 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...