Being Bayesian about Categorical Probability

ICML 2020 Taejong JooUijung ChungMin-Gwan Seo

Neural networks utilize the softmax as a building block in classification tasks, which contains an overconfidence problem and lacks an uncertainty representation ability. As a Bayesian alternative to the softmax, we consider a random variable of a categorical probability over class labels... (read more)

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