This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that consid...
—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...
Wild populations of organism are often difficult to study in their natural settings. Often, it is possible to infer mating information about these species by genotyping the offspri...
Saad I. Sheikh, Ashfaq A. Khokhar, Tanya Y. Berger...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (m...