A Pragmatic Bayesian Approach to Predictive Uncertainty
We describe an approach to regression based on building a probabilistic model with the aid of visualization. The “stereopsis” data set in the predictive uncertainty challenge is used as a case study, for which we constructed a mixture of neural network experts model. We describe both the ideal Bayesian approach and computational shortcuts required to obtain timely results.
KeywordsMarkov Chain Monte Carlo Loss Function Input Space Predictive Distribution Markov Chain Monte Carlo Method
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