The probabilistic network technology is a knowledgebased technique which focuses on reasoning under uncertainty. Because of its well defined semantics and solid theoretical founda...
Methods for cleaning up (or recognizing) states of a neural network are crucial for the functioning of many neural cognitive models. For example, Vector Symbolic Architectures pro...
Terrence C. Stewart, Yichuan Tang, Chris Eliasmith
—Role-based Access Control (RBAC) is one of the most widespread security mechanisms in use today. Given the growing complexity of policy languages and access control systems, ver...
This paper is part of a project to match descriptions of real-world instances and probabilistic models, both of which can be described at mulvel of abstraction and detail. We use ...
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...