11 citations · 19 across the 10 of their papers we have counts for
3 papers · 1 filter
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference
Nikita Durasov, Nik Dorndorf, Hieu Le +1
Whereas the ability of deep networks to produce useful predictions has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approa…
DEBOSH: Deep Bayesian Shape Optimization
Nikita Durasov, Artem Lukoyanov, Jonathan Donier +1
Graph Neural Networks (GNNs) can predict the performance of an industrial design quickly and accurately and be used to optimize its shape effectively. However, to fully explore the…
Masksembles for Uncertainty Estimation
Nikita Durasov, Timur Bagautdinov, Pierre Baque +1
Deep neural networks have amply demonstrated their prowess but estimating the reliability of their predictions remains challenging. Deep Ensembles are widely considered as being on…