The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intract...
Object identification—the task of deciding that two observed objects are in fact one and the same object—is a fundamental requirement for any situated agent that reasons about...
This paper investigates the role of existing "probabilistic" schemes to reason about various everyday situations on the basis of data from multiple heterogeneous physical...
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...