The Language of Uncertainty | Uncertainty in Deep Learning
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چکیده
To formalise our discussion of model uncertainty we will rely on probabilistic modelling, and more specifically on Bayesian modelling. Bayesian probability theory offers us the machinery we need to develop our tools. Together with techniques for approximate inference in Bayesian models, in the next chapter we will present the main results of this work. But prior to that, let us review the main ideas underlying Bayesian modelling, approximate inference, and a model of key importance to us: the Bayesian neural network.
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