3 papers
stat.ML2026
The Manokhin Probability Matrix: A Diagnostic Framework for Classifier Probability Quality
Valery Manokhin
The Brier score conflates two distinct properties of probabilistic predictions: reliability (calibration error) and resolution (discriminatory power). We introduce the Manokhin Pro…
stat.ML2026
Training-Free Probabilistic Time-Series Forecasting with Conformal Seasonal Pools
Valery Manokhin
We propose Conformal Seasonal Pools (CSP), a training-free probabilistic time-series forecaster that mixes same-season empirical draws with signed residual draws around a seasonal…
cs.LG2026
Classifier Calibration at Scale: An Empirical Study of Model-Agnostic Post-Hoc Methods
Valery Manokhin, Daniel Grønhaug
We study model-agnostic post-hoc calibration methods intended to improve probabilistic predictions in supervised binary classification on real i.i.d. tabular data, with particular…