Single-Model Uncertainties for Deep Learning

Single-Model Uncertainties for Deep Learning

2 November 2018

Natasa Tagasovska

David Lopez-Paz

Papers citing "Single-Model Uncertainties for Deep Learning"

12 / 12 papers shown

Title
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference N. Durasov Nik Dorndorf Hieu M. Le Pascal Fua UQCV 30 10 0 21 Nov 2022
DEBOSH: Deep Bayesian Shape Optimization N. Durasov Artem Lukoyanov Jonathan Donier Pascal Fua UQCV AI4CE 38 15 0 28 Sep 2021
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models Jeroen van Hoof Joaquin Vanschoren BDL 38 9 0 06 Jan 2021
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors Jayaraman J. Thiagarajan Bindya Venkatesh P. Sattigeri P. Bremer UQCV 25 31 0 09 Sep 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 32 14 0 26 Aug 2019
Quality of Uncertainty Quantification for Bayesian Neural Network Inference Jiayu Yao Weiwei Pan S. Ghosh Finale Doshi-Velez UQCV BDL 24 113 0 24 Jun 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 268 0 13 Jun 2018
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 232 201 0 06 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
From Dependence to Causation David Lopez-Paz OOD CML 58 25 0 12 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,639 0 03 Jul 2012