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Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review
interactive activation context in perception neural networks probabilistic computation generative models
2015/6/23
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...
Toward a theory of information processing in graded,random,interactive networks
information processing in graded random interactive networks
2015/6/19
Toward a theory of information processing in graded,random,interactive networks.
Learning continuous probability distributions with symmetric diffusion networks
continuous probability distributions symmetric diffusion networks
2015/6/19
Learning continuous probability distributions with symmetric diffusion networks.
Graded state machines:The representation of temporal contingencies in simple recurrent networks
Graded state machines temporal contingencies simple recurrent networks
2015/6/19
Graded state machines:The representation of temporal contingencies in simple recurrent networks.
Finite state automata and simple recurrent networks
Finite state automata simple recurrent networks
2015/6/19
Finite state automata and simple recurrent networks.
Encoding sequential structure in simple recurrent networks
Encoding sequential recurrent networks
2015/6/19
Encoding sequential structure in simple recurrent networks.
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
Natural Scenes Natural Language Recursive Neural Networks
2015/6/12
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...
Hidden Feature Models for Speech Recognition Using Dynamic Bayesian Networks
Hidden Feature Models Speech Recognition Dynamic Bayesian Networks
2014/11/27
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...
Community Detection on Weighted Networks: A Variational Bayesian Method（图）
Community Detection Weighted Networks
2015/1/24
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...