Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Our ability to generate ever-larger, increasingly-complex data, has established the need for scalable methods that identify, and provide insight into, important variable trends and...
Luke J. Gosink, John C. Anderson, E. Wes Bethel,...
Recent improvements in design verification strive to automate error detection and greatly enhance engineers' ability to detect functional errors. However, the process of diag...
We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape c...
Dan A. Alcantara, Owen T. Carmichael, Eric Delson,...
Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular tools for summarization and manifold discovery in discrete data. However, LDA does not ca...