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» Explaining inferences in Bayesian networks
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JMLR
2012
11 years 10 months ago
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Martin Schiegg, Marion Neumann, Kristian Kersting
BMCBI
2005
178views more  BMCBI 2005»
13 years 7 months ago
A quantization method based on threshold optimization for microarray short time series
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
ICPR
2008
IEEE
14 years 2 months ago
2D and 3D upper body tracking with one framework
We propose a Dynamic Bayesian Network (DBN) model for upper body tracking. We first construct a Bayesian Network (BN) to represent the human upper body structure and then incorpo...
Lei Zhang, Jixu Chen, Zhi Zeng, Qiang Ji
IUI
2004
ACM
14 years 1 months ago
Choosing when to interact with learners
In this paper, we describe a method for pedagogical agents to choose when to interact with learners in interactive learning environments. This method is based on observations of h...
Lei Qu, Ning Wang, W. Lewis Johnson
IJCV
2007
134views more  IJCV 2007»
13 years 7 months ago
Multi-sensory and Multi-modal Fusion for Sentient Computing
This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sent...
Christopher Town