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» Bayesian learning of measurement and structural models
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BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
Aki Vehtari, Ville-Petteri Mäkinen, Pasi Soin...
DIS
2010
Springer
13 years 6 months ago
Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships
Quantitative structure-activity relationships (QSARs) are regression models relating chemical structure to biological activity. Such models allow to make predictions for toxicologi...
Ulrich Rückert, Tobias Girschick, Fabian Buch...
AAAI
2006
13 years 9 months ago
A Characterization of Interventional Distributions in Semi-Markovian Causal Models
We offer a complete characterization of the set of distributions that could be induced by local interventions on variables governed by a causal Bayesian network of unknown structu...
Jin Tian, Changsung Kang, Judea Pearl
ICML
2009
IEEE
14 years 8 months ago
A Bayesian approach to protein model quality assessment
Given multiple possible models b1, b2, . . . bn for a protein structure, a common sub-task in in-silico Protein Structure Prediction is ranking these models according to their qua...
Hetunandan Kamisetty, Christopher James Langmead
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...