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IJCNN
2000
IEEE
15 years 8 months ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
137
Voted
ISBI
2002
IEEE
15 years 8 months ago
Bayesian clustering methods for morphological analysis of MR images
Determining the relationship between structure (i.e. morphology) and function is a fundamental problem in brain research. In this paper we present a new framework based on Bayesia...
Hanchuan Peng, Edward Herskovits, Christos Davatzi...
AAAI
1996
15 years 5 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt
ICML
2005
IEEE
16 years 4 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
ICCD
2002
IEEE
160views Hardware» more  ICCD 2002»
16 years 25 days ago
Modeling Switching Activity Using Cascaded Bayesian Networks for Correlated Input Streams
We represent switching activity in VLSI circuits using a graphical probabilistic model based on Cascaded Bayesian Networks (CBN’s). We develop an elegant method for maintaining ...
Sanjukta Bhanja, N. Ranganathan