Looking at the posterior: accuracy and uncertainty of neural-network predictions

no code implementations • 26 Nov 2022 • H. Linander, O. Balabanov, H. Yang, B. Mehlig

Here we show that prediction accuracy depends on both epistemic and aleatoric uncertainty in an intricate fashion that cannot be understood in terms of marginalized uncertainty distributions alone.

Active Learning Bayesian Inference +2