Parameter learning of stochastic Boolean networks
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DOI: 10.1002/rnc.5755
Abstract: In this article, the parameter learning problem is studied for stochastic Boolean networks (SBNs). Both the measure noise and the system noise are assumed to be white and modeled by sequences of Bernoulli distributed stochastic… read more here.
Keywords: boolean networks; parameter learning; stochastic boolean; learning stochastic ... See more keywords
Differentiating between Bayesian parameter learning and structure learning based on behavioural and pupil measures
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DOI: 10.1371/journal.pone.0270619
Abstract: Within predictive processing two kinds of learning can be distinguished: parameter learning and structure learning. In Bayesian parameter learning, parameters under a specific generative model are continuously being updated in light of new evidence. However,… read more here.
Keywords: learning structure; parameter learning; structure learning; phase ... See more keywords
Parameter Learning of Bayesian Network with Multiplicative Synergistic Constraints
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DOI: 10.3390/sym14071469
Abstract: Learning the conditional probability table (CPT) parameters of Bayesian networks (BNs) is a key challenge in real-world decision support applications, especially when there are limited data available. The traditional approach to this challenge is introducing… read more here.
Keywords: bayesian network; synergistic constraints; parameter learning; multiplicative synergistic ... See more keywords