On the relative expressiveness of Bayesian and neural networks

A Choi, R Wang, A Darwiche - International Journal of Approximate …, 2019 - Elsevier
A neural network computes a function. A central property of neural networks is that they are
“universal approximators:” for a given continuous function, there exists a neural network that
can approximate it arbitrarily well, given enough neurons (and some additional
assumptions). In contrast, a Bayesian network is a model, but each of its queries can be
viewed as computing a function. In this paper, we identify some key distinctions between the
functions computed by neural networks and those by marginal Bayesian network queries …

On the relative expressiveness of bayesian and neural networks

A Choi, A Darwiche - International Conference on …, 2018 - proceedings.mlr.press
A neural network computes a function. A central property of neural networks is that they are
“universal approximators:” for a given continuous function, there exists a neural network that
can approximate it arbitrarily well, given enough neurons (and some additional
assumptions). In contrast, a Bayesian network is a model, but each of its queries can be
viewed as computing a function. In this paper, we identify some key distinctions between the
functions computed by neural networks and those by Bayesian network queries, showing …
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