Bayesian logic is a type of statistical analysis that can quantify an uncertain outcome by determining its probability of occurrence using previously known, related data. Bayesian filters are used ...

You need Bayes’ theorem.” Indeed, one reason Bayesian logic is more robust than its frequentist alternative is that it accounts for frequentist sampling. But where do we get these priors from?

Directed acyclic graph (DAG) models—also called Bayesian networks—are widely used in probabilistic reasoning, machine learning and causal inference. If latent variables are present, then the set of ...

Carter T. Butts, BAYESIAN META-ANALYSIS OF SOCIAL NETWORK DATA VIA CONDITIONAL UNIFORM GRAPH QUANTILES, Sociological Methodology, Vol. 41 (2011), pp. 257-298 ...

On Thursday the 21st of November 2019, M.Sc. Topi Talvitie will defend his doctoral thesis on Counting and Sampling Directed Acyclic Graphs for Learning Bayesian Networks. The thesis is a part of ...

Bayesian forecasting and analysis is now mainstream and is used very successfully in many fields. Autonomy, owned by Hewlett- Packard, is based on Bayesian logic.