Many scheduling problems reside in uncertain and dynamic environments – tasks have a nonzero probability of failure and may need to be rescheduled. In these cases, an optimized ...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...
In recent years the Markov Random Field (MRF) has
become the de facto probabilistic model for low-level vision
applications. However, in a maximum a posteriori
(MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
Background: The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein e...
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
—The emergent role of information theory in image formation is surveyed. Unlike the subject of information-theoretic communication theory, information-theoretic imaging is far fr...
Joseph A. O'Sullivan, Richard E. Blahut, Donald L....