68 search results - page 6 / 14 » On the Complexity of Probabilistic Inference in Singly Conne... |
INFFUS
2010
13 years 5 months ago
2010
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
CMSB
2009
Springer
14 years 1 months ago
2009
Springer
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
IJCAI
2003
13 years 8 months ago
2003
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
ICML
2010
IEEE
13 years 8 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...