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BMCBI
2010
229views more  BMCBI 2010»
13 years 5 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
BMCBI
2008
214views more  BMCBI 2008»
13 years 3 months ago
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Jukka Corander, Pekka Marttinen, Jukka Siré...
JCB
2008
106views more  JCB 2008»
13 years 5 months ago
Statistics of Random Protein Superpositions: p-Values for Pairwise Structure Alignment
Quantification of statistical significance is essential for the interpretation of protein structural similarity. To address this, a random model for protein structure comparison w...
James O. Wrabl, Nick V. Grishin
COLING
2000
13 years 6 months ago
Improving SMT quality with morpho-syntactic analysis
In the framework of statistical machine translation (SMT), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis ...
Sonja Nießen, Hermann Ney
JMLR
2010
140views more  JMLR 2010»
13 years 1 days ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink