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This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interac...
The Handbook of Brain Theory and Neural Networks.
Toward a theory of information processing in graded,random,interactive networks.
Graded state machines:The representation of temporal contingencies in simple recurrent networks.
Encoding sequential structure in simple recurrent networks.
Recursive structure is commonly found in the inputs of different modalities such as natural scene images or natural language sentences. Discovering this recursive structure helps us to not only identi...
Current views on the neurobiological underpinnings oflanguage are discussed that deviate in a number of ways from the classical Wernicke–Lichtheim–Geschwind model. More areas than Broca’s and Wernicke...
In this paper, we investigate the use of dynamic Bayesian networks (DBNs) to explicitly represent models of hidden features,such as articulatory or other phonological features, for automatic speech re...
Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way for better understanding the pr...

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