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20222025
most citedDBCal: Density Based Calibration of classifier predictions for uncertainty quantification

3 citations · 7 across the 7 of their papers we have counts for

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physics.data-an2022

Reduction of detection limit and quantification uncertainty due to interferent by neural classification with abstention

Alex Hagen, Ken Jarman, Jesse Ward +5

Many measurements in the physical sciences can be cast as counting experiments, where the number of occurrences of a physical phenomenon informs the prevalence of the phenomenon's…

stat.ML2022★ 3 cited

DBCal: Density Based Calibration of classifier predictions for uncertainty quantification

Alex Hagen, Karl Pazdernik, Nicole LaHaye +1

Measurement of uncertainty of predictions from machine learning methods is important across scientific domains and applications. We present, to our knowledge, the first such techni…