—Models of regulatory networks become more difficult to construct and understand as they grow in size and complexity. Large models are usually built up from smaller models, repre...
Ranjit Randhawa, Clifford A. Shaffer, John J. Tyso...
This paper aims to propose an extension of SOMs called an “SOM of SOMs,” or SOM¾ , in which the mapped objects are self-organizing maps themselves. In SOM¾ , each nodal unit ...
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Abstract. Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in vid...
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...