Bayesian dark knowledge Bayesian dark knowledge
Paper summary It's not clear to me how predicting the variance with a neural network is a robust estimator of uncertainty. We all know the adversarial examples where we can simply fool a neural network with an example that is a little off. By a same argument, we could make adversarial examples to _fool_ the uncertainty estimator. I would like to see more work on this

Summary from Hugo Larochelle
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Summary from robromijnders
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