8 citations · 8 across the 1 of their papers we have counts for
2 papers
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…
stat.ML2020
NCVis: Noise Contrastive Approach for Scalable Visualization
Aleksandr Artemenkov, Maxim Panov
Modern methods for data visualization via dimensionality reduction, such as t-SNE, usually have performance issues that prohibit their application to large amounts of high-dimensio…