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NIPS
1998
14 years 11 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
BMCBI
2007
173views more  BMCBI 2007»
14 years 10 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
CGF
2010
193views more  CGF 2010»
14 years 10 months ago
Accelerated Visualization of Dynamic Molecular Surfaces
Molecular surfaces play an important role in studying the interactions between molecules. Visualizing the dynamic behavior of molecules is particularly interesting to gain insight...
Norbert Lindow, Daniel Baum, Steffen Prohaska, Han...
IJAR
2008
118views more  IJAR 2008»
14 years 10 months ago
Dynamic multiagent probabilistic inference
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Xiangdong An, Yang Xiang, Nick Cercone
ICRA
2010
IEEE
104views Robotics» more  ICRA 2010»
14 years 8 months ago
Using model knowledge for learning inverse dynamics
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
Duy Nguyen-Tuong, Jan Peters