Teaching and learning materials
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Aaron Roth, University of Pennsylvania
A course for PhD students addressing "modern techniques in machine learning, statistics, and computer science for estimating the uncertainty of black box forecasts. This includes conformal prediction, calibration and multi-calibration, outcome indistinguishability, and recent techniques for producing worst-case empirical coverage guarantees without any distributional assumptions." Includes a full set of lecture videos and links to readings.