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Correlated measurements are interpreted better with machine learning

What is it about?

This research is about predicting the uncertainty of crystallographic measurements. Uncertainty can be under- and overestimated and this is not desirable. When we also consider the correlation of measurement the estimate for uncertainty becomes more accurate.

Why is it important?

Predicting the range of future measurements and assisting modeling tools that rely on accurate uncertainty.

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The following have contributed to this page:
Gergely Katona
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