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» Incremental Bayesian networks for structure prediction
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ICML
2009
IEEE
14 years 7 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
UAI
2003
13 years 8 months ago
Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
Darya Chudova, Scott Gaffney, Padhraic Smyth
BMCBI
2006
133views more  BMCBI 2006»
13 years 6 months ago
Choosing negative examples for the prediction of protein-protein interactions
The protein-protein interaction networks of even well-studied model organisms are sketchy at best, highlighting the continued need for computational methods to help direct experim...
Asa Ben-Hur, William Stafford Noble
BMCBI
2010
174views more  BMCBI 2010»
13 years 6 months ago
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based h
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...
Junbai Wang
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
14 years 1 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...