175 search results - page 2 / 35 » Learning Continuous Time Bayesian Networks |
JMLR
2010
12 years 12 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
CVPR
1999
IEEE
14 years 7 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
ICML
1996
IEEE
14 years 6 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
EUSFLAT
2003
13 years 6 months ago
2003
This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The dat...