Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions

29 Jun 2020Ahmed M. AlaaMihaela van der Schaar

Deep learning models achieve high predictive accuracy across a broad spectrum of tasks, but rigorously quantifying their predictive uncertainty remains challenging. Usable estimates of predictive uncertainty should (1) cover the true prediction targets with high probability, and (2) discriminate between high- and low-confidence prediction instances... (read more)

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