We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict ...
Traditional Non-Negative Matrix Factorization (NMF) [19] is a successful algorithm for decomposing datasets into basis function that have reasonable interpretation. One problem of...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
Establishing and accessing a reliable communication infrastructure at crisis site is a challenging research problem. Failure in communication infrastructure and information exchang...
We introduce the model of Markov nets, a probabilistic extension of safe Petri nets under the true-concurrency semantics--this means that traces, not firing sequences, are given a...
Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...