Conspiracy theories cover topics from politicians to world events. Frequently, proponents of conspiracies hold these beliefs strongly despite available evidence that may challenge or disprove them. Therefore, conspiratorial reasoning has often been described as illegitimate or flawed. In the paper, we explore the possibility of growing a rational (Bayesian) conspiracy theorist through an Agent-...

121 Generalized Versions of Turbo Decoding in the Framework of Bayesian Networks and Pearl's Belief Propagation Algorithm Peyman Meshkat and John D. Villasenor Electrical Engineering Department University of California, Los Angeles Abstract| We use the framework of Bayesian networks to introduce generalizations of the traditional turbo decoding algorithm. We show that traditional turbo decoding...

There is a critical need for data-mining methods that can identify SNPs that predict among individual variation in a phenotype of interest and reverse-engineer the biological network of relationships between SNPs, phenotypes, and other factors. This problem is both challenging and important in light of the large number of SNPs in many genes of interest and across the human genome. A potentially...

This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and appro...

PANSOMBUT, TATDOW. Advanced Learning Techniques for Improved Inference of Bayesian Belief Networks from Uncertain and High-dimensional Data. (Under the direction of Prof. Nagiza F. Samatova and Prof. Dennis R. Bahler.) A Bayesian Belief Network (BBN) is a powerful probabilistic learning model, it has been used successfully in many problem domains, such as medical diagnostics, computational biol...

We review a logic-based modeling language PRISM and report recent developments including belief propagation by the generalized inside-outside algorithm and generative modeling with constraints. The former implies PRISM subsumes belief propagation at the algorithmic level. We also compare the performance of PRISM with state-of-theart systems in statistical natural language processing and probabi...