Yoel Zeldes • 8/6/2018

Neural Networks from a Bayesian Perspective

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This technical article explains how to interpret neural networks from a Bayesian perspective to model uncertainty. It covers Bayesian learning fundamentals, contrasts MLE and MAP estimation, and introduces the concept of learning a distribution over weights instead of a single set, enabling better uncertainty quantification in deep learning models.

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#Neural Networks #Deep Learning #Bayesian Statistics
Neural Networks from a Bayesian Perspective

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