This contribution presents a new class of MRF, that is inspired by methods of statistical physics. The new energy function assumes full-connectivity in the neighborhood system and...
Concurrent and distributed systems have traditionally been modelled using nondeterministic transitions over configurations. The minism provides an abstraction over scheduling, net...
This paper describes the development and structure of a second course in artificial intelligence that was developed to meet the needs of upper-division undergraduate and graduate ...
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
In designing a Bayesian network for an actual problem, developers need to bridge the gap between ematical abstractions offered by the Bayesian-network formalism and the features o...