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Kaspar Valk

1 paper hereh-index 210 citations2 works total

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author position
  • middle author1

Across the 1 of 1 paper where every author was matched, so the position is known.

fields
  • cs.LG1

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most citedOn the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2022★ 2 cited

On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers

Markus Kängsepp, Kaspar Valk, Meelis Kull

Every uncalibrated classifier has a corresponding true calibration map that calibrates its confidence. Deviations of this idealistic map from the identity map reveal miscalibration…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.