Improving robustness and calibration in ensembles with diversity regularization

26 January 2022

Papers citing "Improving robustness and calibration in ensembles with diversity regularization"

8 / 8 papers shown

Title
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis OOD UQCV 12 2 0 08 Apr 2023
Joint Training of Deep Ensembles Fails Due to Learner Collusion Alan Jeffares Tennison Liu Jonathan Crabbé M. Schaar FedML 44 15 0 26 Jan 2023
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 27 5 0 15 Dec 2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation Martin Ferianc Miguel R. D. Rodrigues UQCV 37 0 0 19 May 2022
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling Kirill Fedyanin Evgenii Tsymbalov Maxim Panov UQCV 11 7 0 06 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 282 9,136 0 06 Jun 2015
Determinantal point processes for machine learning Alex Kulesza B. Taskar 160 1,122 0 25 Jul 2012