Corpus ID: 61284485

Continuous Time Bayesian Networks for Inferring Users’ Presence and Activities with Extensions for Modeling and Evaluation

@inproceedings{Nodelman2003ContinuousTB,
  title={Continuous Time Bayesian Networks for Inferring Users’ Presence and Activities with Extensions for Modeling and Evaluation},
  author={U. Nodelman and E. Horvitz},
  year={2003}
}
Continuous time Bayesian networks (CTBNs) represent structured stochastic processes that evolve over continuous time. The methodology is based on earlier work on homogenous Markov processes, extended to capture dependencies among variables representing continuous time processes. We have worked to apply CTBNs to the challenge of reasoning about users’ presence and availability over time. As part of this research, we extended the methodology of CTBNs to allow a large class of phase distributions… Expand
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Learning Continuous Time Bayesian Networks
Continuous Time Bayesian Networks