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» Bayesian Structure from Motion
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ICASSP
2010
IEEE
15 years 28 days ago
Sparse Bayesian step-filtering for high-throughput analysis of molecular machine dynamics
Nature has evolved many molecular machines such as kinesin, myosin, and the rotary flagellar motor powered by an ion current from the mitochondria. Direct observation of the step-...
Max A. Little, Nick S. Jones
AAAI
2006
15 years 2 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
107
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ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 11 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
115
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AUSAI
2006
Springer
15 years 4 months ago
Learning Hybrid Bayesian Networks by MML
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Rodney T. O'Donnell, Lloyd Allison, Kevin B. Korb
111
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CRV
2009
IEEE
217views Robotics» more  CRV 2009»
15 years 7 months ago
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...