Universal spin models are universal approximators of probability distributions, yielding a unified recipe for universal approximation theorems in models such as restricted Boltzmann machines and deep belief networks.
Cybenko, Approximation by superpositions of a sig- moidal function, Mathematics of Control, Signals and Systems 2, 303 (1989)
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Universal Spin Models are Universal Approximators in Machine Learning
Universal spin models are universal approximators of probability distributions, yielding a unified recipe for universal approximation theorems in models such as restricted Boltzmann machines and deep belief networks.