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Yes, this is the best I've seen too. Unfortunately, "quickly" is a matter of perspective.

Usually you train a neural net that's as large as possible with a runtime that's within your latency and GPU budget. Running the net even twice will blow up your budget.

Also, I haven't seen a great evaluation on how well this method works in practice. For example, how well does predicted uncertainty capture mistakes on a real-world dataset?

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