43 citations · 153 across the 27 of their papers we have counts for
3 papers · 2 filters
Scalable computation of prediction intervals for neural networks via matrix sketching
Alexander Fishkov, Maxim Panov
Accounting for the uncertainty in the predictions of modern neural networks is a challenging and important task in many domains. Existing algorithms for uncertainty estimation requ…
Embedded Ensembles: Infinite Width Limit and Operating Regimes
Maksim Velikanov, Roman Kail, Ivan Anokhin +4
A memory efficient approach to ensembling neural networks is to share most weights among the ensembled models by means of a single reference network. We refer to this strategy as E…
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network
Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin +6
This paper proposes a fast and scalable method for uncertainty quantification of machine learning models' predictions. First, we show the principled way to measure the uncertainty…