Training independent subnetworks for robust prediction
Recent approaches to efficiently ensemble neural networks have shown that strong
robustness and uncertainty performance can be achieved with a negligible gain in …
robustness and uncertainty performance can be achieved with a negligible gain in …
Training independent subnetworks for robust prediction
M Havasi, R Jenatton, S Fort, J Liu… - research.google
Recent approaches to efficiently ensemble neural networks have shown that strong
robustness and uncertainty performance can be achieved with a negligible gain in …
robustness and uncertainty performance can be achieved with a negligible gain in …
Training independent subnetworks for robust prediction
M Havasi, R Jenatton, S Fort, J Zhe Liu… - arXiv e …, 2020 - ui.adsabs.harvard.edu
Recent approaches to efficiently ensemble neural networks have shown that strong
robustness and uncertainty performance can be achieved with a negligible gain in …
robustness and uncertainty performance can be achieved with a negligible gain in …
Training independent subnetworks for robust prediction
M Havasi, R Jenatton, S Fort, JZ Liu, J Snoek… - … Conference on Learning … - openreview.net
Recent approaches to efficiently ensemble neural networks have shown that strong
robustness and uncertainty performance can be achieved with a negligible gain in …
robustness and uncertainty performance can be achieved with a negligible gain in …
Training independent subnetworks for robust prediction
M Havasi, R Jenatton, S Fort, J Liu, JR Snoek… - research.google
Recent approaches to efficiently ensemble neural networks have shown that strong
robustness and uncertainty performance can be achieved with a negligible gain in …
robustness and uncertainty performance can be achieved with a negligible gain in …