We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
Motivated by applications such as the spread of epidemics and the propagation of influence in social networks, we propose a formal model for analyzing the dynamics of such networ...
Christopher L. Barrett, Harry B. Hunt III, Madhav ...
—Most research works in routing and design of optical networks assume that the optical medium can carry signals without any bit error. However, the physical impairments on the op...
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Model is a kind of codified knowledge that has been verified in solving problems. Solving a complex problem usually needs a set of models. Using components, the composition of a s...