18 citations · 21 across the 6 of their papers we have counts for
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stat.ML2023★ 1 cited
Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ?
Pascal Pernot
Binwise Variance Scaling (BVS) has recently been proposed as a post hoc recalibration method for prediction uncertainties of machine learning regression problems that is able of mo…
stat.ML2023★ 18 cited
Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity
Pascal Pernot
Reliable uncertainty quantification (UQ) in machine learning (ML) regression tasks is becoming the focus of many studies in materials and chemical science. It is now well understoo…