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JMLR
2010
14 years 4 months ago
2010
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
ECSQARU
2005
Springer
15 years 3 months ago
2005
Springer
In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function for t...
NN
1997
Springer
15 years 1 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
IJAR
2008
14 years 9 months ago
2008
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
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ICIP
2008
IEEE
15 years 4 months ago
2008
IEEE
In this paper we propose a novel algorithm for super resolution based on total variation prior and variational distribution approximations. We formulate the problem using a hierar...