Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings

18 November 2021

Papers citing "Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings"

13 / 13 papers shown

Title
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 224 1,147 0 07 Jul 2021
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving Di Feng Ali Harakeh Steven Waslander Klaus C. J. Dietmayer AAML UQCV EDL 69 226 0 20 Nov 2020
The Case for Bayesian Deep Learning A. Wilson UQCV BDL OOD 107 112 0 29 Jan 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 222 1,410 0 21 Oct 2019
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks Aryan Mobiny H. Nguyen S. Moulik Naveen Garg Carol C. Wu UQCV BDL 52 161 0 07 Jun 2019
Classification Uncertainty of Deep Neural Networks Based on Gradient Information Philipp Oberdiek Matthias Rottmann Hanno Gottschalk UQCV 56 64 0 22 May 2018
The Limits and Potentials of Deep Learning for Robotics Niko Sünderhauf Oliver Brock Walter J. Scheirer R. Hadsell Dieter Fox ... B. Upcroft Pieter Abbeel Wolfram Burgard Michael Milford Peter Corke 73 528 0 18 Apr 2018
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches Yeming Wen Paul Vicol Jimmy Ba Dustin Tran Roger C. Grosse BDL 47 311 0 12 Mar 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 291 5,825 0 14 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 352 4,704 0 15 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 820 5,806 0 05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 155 3,451 0 07 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 813 9,302 0 06 Jun 2015