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NIPS
2008
13 years 8 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
BMCBI
2006
144views more  BMCBI 2006»
13 years 7 months ago
Development and implementation of an algorithm for detection of protein complexes in large interaction networks
Background: After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry e...
Md. Altaf-Ul-Amin, Yoko Shinbo, Kenji Mihara, Ken ...
ISI
2006
Springer
13 years 7 months ago
An Embedded Bayesian Network Hidden Markov Model for Digital Forensics
In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
MST
2006
104views more  MST 2006»
13 years 7 months ago
Sequencing from Compomers: The Puzzle
The board game FragmindTM poses the following problem: The player has to reconstruct an (unknown) string s over the alphabet . To this end, the game reports the following informati...
Sebastian Böcker
CONSTRAINTS
1998
127views more  CONSTRAINTS 1998»
13 years 7 months ago
Experimental Analysis of Numeric and Symbolic Constraint Satisfaction Techniques for Temporal Reasoning
Many temporal applications like planning and scheduling can be viewed as special cases of the numeric and symbolic temporal constraint satisfaction problem. Thus we have developed ...
Malek Mouhoub, François Charpillet, Jean Pa...