Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
to Concepts and Methods

v1v2v3 (latest)

Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

21 October 2019

Eyke Hüllermeier

Willem Waegeman

ArXiv (abs)PDF HTML

Papers citing "Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods"

11 / 61 papers shown

Title
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,847 0 05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 176 3,480 0 07 Oct 2016
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products Kush R. Varshney H. Alemzadeh 134 225 0 05 Oct 2016
Engineering Safety in Machine Learning Kush R. Varshney 84 118 0 16 Jan 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 289 751 0 06 Jun 2015
Consistent Algorithms for Multiclass Classification with a Reject Option H. G. Ramaswamy Ambuj Tewari S. Agarwal 43 25 0 15 May 2015
Generalized Evidence Theory Yong Deng 70 271 0 17 Apr 2014
One-Class Classification: Taxonomy of Study and Review of Techniques Shehroz S. Khan Michael G. Madden 90 569 0 30 Nov 2013
Optimal Uncertainty Quantification H. Owhadi C. Scovel T. Sullivan Michael McKerns M. Ortiz 124 124 0 02 Sep 2010
Unifying Practical Uncertainty Representations: I. Generalized P-Boxes Sebastien Destercke D. Dubois E. Chojnacki 110 128 0 20 Aug 2008
A tutorial on conformal prediction Glenn Shafer V. Vovk 456 1,151 0 21 Jun 2007

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.