Current Bayesian net representations do not consider structure in the domain and include all variables in a homogeneous network. At any time, a human reasoner in a large domain ma...
Abstract. This paper discusses similarities between models of adaptive motor control suggested by recent experiments with human and animal subjects, and the structure of a new cont...
We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher ord...
Sanjukta Bhanja, Karthikeyan Lingasubramanian, N. ...
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...