no code implementations • 3 Feb 2015 • Jason K. Johnson, Diane Oyen, Michael Chertkov, Praneeth Netrapalli
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering.
no code implementations • 27 Jan 2009 • Jason K. Johnson, Danny Bickson, Danny Dolev
It is known that when GaBP converges it converges to the correct MAP estimate of the Gaussian random vector and simple sufficient conditions for its convergence have been established.
no code implementations • NeurIPS 2007 • Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson
We consider the estimation problem in Gaussian graphical models with arbitrary structure.
