A model for reasoning about persistence and causation
Computational Intelligence
Neural networks and the bias/variance dilemma
Neural Computation
Exploiting the architecture of dynamic systems
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Robotics and Autonomous Systems
Factored reasoning for monitoring dynamic team and goal formation
Information Fusion
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
The value of observation for monitoring dynamic systems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Dynamic probabilistic relational models
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Continuous time particle filtering
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Automated compilation of Object-Oriented Probabilistic Relational Models
International Journal of Approximate Reasoning
Information theoretic adaptive tracking of epidemics in complex networks
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Observer for an omnidirectional mobile robot
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
FlexCon: robust context handling in human-oriented pervasive flows
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
A framework for distributed managing uncertain data in RFID traceability networks
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
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Exact monitoring in dynamic Bayesian networks is intractable, so approximate algorithms are necessary. This paper presents a new family of approximate monitoring algorithms that combine the best qualities of the particle filtering and Boyen-Koller methods. Our algorithms maintain an approximate representation the belief state in the form of sets of factored particles, that correspond to samples of clusters of state variables. Empirical results show that our algorithms outperform both ordinary particle filtering and the Boyen-Koller algorithm on large systems.