Bridging calibration and refinement — our latest work at AISTATS!

We present a general method for consistent and asymptotically unbiased estimation of proper calibration errors and refinement terms. Introducing the Kullback–Leibler calibration error, we reveal its connection to f-divergences and information monotonicity in neural networks. Published at the International Conference on Artificial Intelligence and Statistics.