Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
It has already been shown how Artificial Neural Networks (ANNs) can be incorporated into probabilistic models. In this paper we review some of the approaches which have been prop...
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
This paper investigates how behavioral cloning can be used to decrease training time for students learning to y on simulators. The challenges presented to each student must be tai...
Charles W. Anderson, Bruce A. Draper, David A. Pet...