By Liu Ziyin and others

This work theoretically studies stochastic neural networks, a main type of neural network in use. We prove that as the width of an optimized stochastic neural network tends to infinity, its predictive variance on the training set decreases to zero. Our theory justifies the common intuition that adding stochasticity to... Show more

May 24, 2022

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Stochastic Neural Networks with Infinite Width are Deterministic

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