40 citations · 65 across the 10 of their papers we have counts for
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stat.ML2014★ 6 cited
Deep Narrow Boltzmann Machines are Universal Approximators
Guido Montufar
We show that deep narrow Boltzmann machines are universal approximators of probability distributions on the activities of their visible units, provided they have sufficiently many…
stat.ML2014★ 40 cited
Expressive Power and Approximation Errors of Restricted Boltzmann Machines
Guido Montufar, Johannes Rauh, Nihat Ay
We present explicit classes of probability distributions that can be learned by Restricted Boltzmann Machines (RBMs) depending on the number of units that they contain, and which a…
stat.ML2010
Refinements of Universal Approximation Results for Deep Belief Networks and Restricted Boltzmann Machines
Guido Montufar, Nihat Ay
We improve recently published results about resources of Restricted Boltzmann Machines (RBM) and Deep Belief Networks (DBN) required to make them Universal Approximators. We show t…