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AAAI
2006
14 years 8 days ago
Performing Incremental Bayesian Inference by Dynamic Model Counting
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...
Wei Li 0002, Peter van Beek, Pascal Poupart
JAIR
2011
129views more  JAIR 2011»
13 years 5 months ago
Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference
Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an ...
Wei Li 0002, Pascal Poupart, Peter van Beek
ICML
2010
IEEE
13 years 12 months ago
Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
Nicholas Bartlett, David Pfau, Frank Wood
AAAI
2008
14 years 1 months ago
Exploiting Causal Independence Using Weighted Model Counting
Previous studies have demonstrated that encoding a Bayesian network into a SAT-CNF formula and then performing weighted model counting using a backtracking search algorithm can be...
Wei Li 0002, Pascal Poupart, Peter van Beek
BMCBI
2010
136views more  BMCBI 2010»
13 years 11 months ago
Bias correction and Bayesian analysis of aggregate counts in SAGE libraries
Background: Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation proces...
Russell L. Zaretzki, Michael A. Gilchrist, William...