53 citations · 127 across the 7 of their papers we have counts for
7 papers
Variational Learning in Mixed-State Dynamic Graphical Models
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huang
Many real-valued stochastic time-series are locally linear (Gassian), but globally non-linear. For example, the trajectory of a human hand gesture can be viewed as a linear dynamic…
Learning Graphical Models of Images, Videos and Their Spatial Transformations
Brendan J. Frey, Nebojsa Jojic
Mixtures of Gaussians, factor analyzers (probabilistic PCA) and hidden Markov models are staples of static and dynamic data modeling and image and video modeling in particular. We…
A Factorized Variational Technique for Phase Unwrapping in Markov Random Fields
Kannan Achan, Brendan J. Frey, Ralf Koetter
Some types of medical and topographic imaging device produce images in which the pixel values are "phase-wrapped", i.e. measured modulus a known scalar. Phase unwrapping can be vie…
Learning Generative Models of Similarity Matrices
Romer Rosales, Brendan J. Frey
We describe a probabilistic (generative) view of affinity matrices along with inference algorithms for a subclass of problems associated with data clustering. This probabilistic vi…
Extending Factor Graphs so as to Unify Directed and Undirected Graphical Models
Brendan J. Frey
The two most popular types of graphical model are directed models (Bayesian networks) and undirected models (Markov random fields, or MRFs). Directed and undirected models offer co…
Fast Exact Inference for Recursive Cardinality Models
Daniel Tarlow, Kevin Swersky, Richard S. Zemel +2
Cardinality potentials are a generally useful class of high order potential that affect probabilities based on how many of D binary variables are active. Maximum a posteriori (MAP)…