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UAI
2004
13 years 8 months ago
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
Mathias Drton, Thomas S. Richardson
IJCNN
2006
IEEE
14 years 1 months ago
A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...
Yiwen Wang 0002, António R. C. Paiva, Jose ...
ICA
2010
Springer
13 years 8 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
NIPS
2000
13 years 8 months ago
Mixtures of Gaussian Processes
We introduce the mixture of Gaussian processes (MGP) model which is useful for applications in which the optimal bandwidth of a map is input dependent. The MGP is derived from the...
Volker Tresp
ICASSP
2011
IEEE
12 years 11 months ago
Predictive modeling of the spatiotemporal evolution of an environmental hazard and its sensor network implementation
Predicting accurately the spatiotemporal evolution of a diffusive environmental hazard is of paramount importance for its effective containment. We approximate the front line of a...
Dimitris V. Manatakis, Elias S. Manolakos