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CORR
2010
Springer
69views Education» more  CORR 2010»
13 years 7 months ago
Epistemic irrelevance in credal nets: the case of imprecise Markov trees
We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal ne...
Gert de Cooman, Filip Hermans, Alessandro Antonucc...
UAI
2003
13 years 9 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
JMLR
2010
157views more  JMLR 2010»
13 years 2 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
AROBOTS
2008
166views more  AROBOTS 2008»
13 years 6 months ago
User-adapted plan recognition and user-adapted shared control: A Bayesian approach to semi-autonomous wheelchair driving
Abstract Many elderly and physically impaired people experience difficulties when maneuvering a powered wheelchair. In order to provide improved maneuvering, powered wheelchairs ha...
Eric Demeester, Alexander Hüntemann, Dirk Van...
ESANN
2006
13 years 9 months ago
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...