832 citations · 1.3k across the 79 of their papers we have counts for
Showing 2014 · stat.MLShow all
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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.ML2014★ 832 cited
On the Number of Linear Regions of Deep Neural Networks
Guido Montúfar, Razvan Pascanu, Kyunghyun Cho +1
We study the complexity of functions computable by deep feedforward neural networks with piecewise linear activations in terms of the symmetries and the number of linear regions th…