5 search results - page 1 / 1 » Hierarchical explanation of inference in Bayesian networks t... |
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
This paper describes a novel method for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is m...
AAAI
1998
13 years 8 months ago
1998
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
IDEAL
2004
Springer
14 years 22 days ago
2004
Springer
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
AAAI
2008
13 years 9 months ago
2008
Modal logic represents knowledge that agents have about other agents' knowledge. Probabilistic modal logic further captures probabilistic beliefs about probabilistic beliefs....
CVPR
2007
IEEE
2007
IEEE
Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video
14 years 9 months ago
We present a scalable approach to recognizing and describing complex activities in video sequences. We are interested in long-term, sequential activities that may have several par...