3 papers
cond-mat.dis-nn2004
Neural Networks Processing Mean Values of Random Variables
M. J. Barber, J. W. Clark, C. H. Anderson
We introduce a class of neural networks derived from probabilistic models in the form of Bayesian belief networks. By imposing additional assumptions about the nature of the probab…
cond-mat.dis-nn2001
Neural Representation of Probabilistic Information
M. J. Barber, J. W. Clark, C. H. Anderson
It has been proposed that populations of neurons process information in terms of probability density functions (PDFs) of analog variables. Such analog variables range, for example,…
cond-mat.dis-nn2001
Neural Propagation of Beliefs
M. J. Barber, J. W. Clark, C. H. Anderson
We continue to explore the hypothesis that neuronal populations represent and process analog variables in terms of probability density functions (PDFs). A neural assembly encoding…