8 citations · 12 across the 9 of their papers we have counts for
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cs.CV2022
ScaleFace: Uncertainty-aware Deep Metric Learning
Roman Kail, Kirill Fedyanin, Nikita Muravev +2
The performance of modern deep learning-based systems dramatically depends on the quality of input objects. For example, face recognition quality would be lower for blurry or corru…
stat.ML2022★ 8 cited
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…