91 citations · 122 across the 5 of their papers we have counts for
3 papers · 1 filter
Fast and Scalable Score-Based Kernel Calibration Tests
Pierre Glaser, David Widmann, Fredrik Lindsten +1
We introduce the Kernel Calibration Conditional Stein Discrepancy test (KCCSD test), a non-parametric, kernel-based test for assessing the calibration of probabilistic models with…
Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Most supervised machine learning tasks are subject to irreducible prediction errors. Probabilistic predictive models address this limitation by providing probability distributions…
Calibration tests in multi-class classification: A unifying framework
David Widmann, Fredrik Lindsten, Dave Zachariah
In safety-critical applications a probabilistic model is usually required to be calibrated, i.e., to capture the uncertainty of its predictions accurately. In multi-class classific…