Expressive Power of Conditional Restricted Boltzmann Machines
Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi · arXiv (Cornell University) · 2014
Conditional restricted Boltzmann machines are undirected stochastic neural networks with a layer of input and output units connected bipartitely to a layer of hidden units. These networks define models of conditional probability distributions on the states of the output units given the states of the input units, parametrized by interaction weights and biases. We address the representational power of these models, proving results on the minimal size of universal approximators of condi-