77 citations · 144 across the 5 of their papers we have counts for
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stat.ML2020★ 42 cited
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova +2
Test-time data augmentationaveraging the predictions of a machine learning model across multiple augmented samples of datais a widely used technique that improves the predict…
stat.ML2020★ 77 cited
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov +1
Uncertainty estimation and ensembling methods go hand-in-hand. Uncertainty estimation is one of the main benchmarks for assessment of ensembling performance. At the same time, deep…