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Groggolog t1_j7mrxcu wrote

Have you looked at using Conformal Prediction for uncertainty quantification in your ML pipeline? If so why not? It's a technique that has been around for a while but I don't see it massively widely used, though some of the example use cases I have seen were drug discovery NNs.

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IHaque_Recursion t1_j7mzd3e wrote

Conformal prediction is indeed an interesting method (or family thereof). I can’t comment on our undisclosed internal machine learning research, but what I can say is that machine learning on biological problems tends to be much, much harder than that on common toy or benchmarking datasets. Uncertainty quantification is usually an even harder problem than pure accuracy measurement, especially when you have a mix of known and unknown systematic and random effects in your data-generating process.

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