We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
We propose a unified framework for deriving and studying soft-in soft-out (SISO) detection in multiple-access channels using the concept of variational inference. The proposed fram...
Readers of this article have probably seen, at least once, diagrams produced using the UML (Unified Modeling Language). Some of you have perhaps used UML for your own work and kno...
A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded resp...
Enrique Carlos Segura Meccia, Roberto P. J. Perazz...
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...