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BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
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
ICML
2008
IEEE
14 years 8 months ago
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity
Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous effects. Estimation of Gaussian ...
Aapo Hyvärinen, Patrik O. Hoyer, Shohei Shimi...
IROS
2007
IEEE
148views Robotics» more  IROS 2007»
14 years 2 months ago
Tractable probabilistic models for intention recognition based on expert knowledge
— Intention recognition is an important topic in human-robot cooperation that can be tackled using probabilistic model-based methods. A popular instance of such methods are Bayes...
Oliver C. Schrempf, David Albrecht, Uwe D. Hanebec...
IJCAI
2001
13 years 9 months ago
Leveraging Data About Users in General in the Learning of Individual User Models
Models of computer users that are learned on the basis of data can make use of two types of information: data about users in general and data about the current individual user. Fo...
Anthony Jameson, Frank Wittig