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

21 October 2019

Eyke Hüllermeier

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

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RMBR: A Regularized Minimum Bayes Risk Reranking Framework for Machine Translation Yidan Zhang Boyi Deng Dayiheng Liu Baosong Yang Zhenan He 24 2 0 01 Mar 2022
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LiDAR dataset distillation within bayesian active learning framework: Understanding the effect of data augmentation Ngoc Phuong Anh Duong Alexandre Almin Léo Lemarié B. R. Kiran 13 3 0 06 Feb 2022
Sketching stochastic valuation functions M. C. Yiliu Wang 17 0 0 01 Feb 2022
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs Philipp Oberdiek G. Fink Matthias Rottmann OODD 32 14 0 31 Jan 2022
Uncertainty-aware Pseudo-label Selection for Positive-Unlabeled Learning Emilio Dorigatti Jann Goschenhofer B. Schubert Mina Rezaei Bernd Bischl 18 3 0 31 Jan 2022
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Learning Curves for Decision Making in Supervised Machine Learning: A Survey F. Mohr Jan N. van Rijn 38 53 0 28 Jan 2022
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Analytic Mutual Information in Bayesian Neural Networks J. Woo UQCV 25 6 0 24 Jan 2022
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models Pascal Gerber Lisa Jöckel Michael Kläs 25 4 0 10 Jan 2022
Similarities and Differences between Machine Learning and Traditional Advanced Statistical Modeling in Healthcare Analytics Michele Bennett K. Hayes Ewa J. Kleczyk, PhD Rajesh Mehta 11 14 0 07 Jan 2022
Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT Aparna Elangovan Yuan Li Douglas E. V. Pires Melissa J. Davis Karin Verspoor 18 8 0 06 Jan 2022
The intersection probability: betting with probability intervals F. Cuzzolin 19 3 0 05 Jan 2022
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation Vincent Mai Kaustubh Mani Liam Paull 33 34 0 05 Jan 2022
Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression John Jackson Luca Laurenti Eric Frew Morteza Lahijanian 10 16 0 31 Dec 2021
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Classification Under Ambiguity: When Is Average-K Better Than Top-K? Titouan Lorieul Alexis Joly Dennis Shasha 19 1 0 16 Dec 2021
Prescriptive Machine Learning for Automated Decision Making: Challenges and Opportunities Eyke Hüllermeier 10 5 0 15 Dec 2021
Uncertainty estimation under model misspecification in neural network regression Maria R. Cervera Rafael Dätwyler Francesco DÁngelo Hamza Keurti Benjamin Grewe Christian Henning 28 6 0 23 Nov 2021
Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model Jing Zhang Yuchao Dai Mehrtash Harandi Yiran Zhong Nick Barnes Richard I. Hartley UQCV 18 1 0 22 Nov 2021
Deep Probability Estimation Sheng Liu Aakash Kaku Weicheng Zhu M. Leibovich S. Mohan ... Haoxiang Huang L. Zanna N. Razavian Jonathan Niles-Weed C. Fernandez‐Granda UQCV OOD 28 14 0 21 Nov 2021
Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings Matias Valdenegro-Toro UQCV 23 2 0 18 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 19 58 0 03 Nov 2021
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data Junjiao Tian Yen-Change Hsu Yilin Shen Hongxia Jin Z. Kira OODD 19 6 0 28 Oct 2021
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification Romain Egele R. Maulik Krishnan Raghavan Bethany Lusch Isabelle M Guyon Prasanna Balaprakash UQCV OOD BDL 20 45 0 26 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang H. Lam Haofeng Zhang UQCV BDL UD PER 16 12 0 23 Oct 2021
Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty Christoph Jansen Hannah Blocher Thomas Augustin G. Schollmeyer 11 13 0 19 Oct 2021
Efficient Exploration in Binary and Preferential Bayesian Optimization T. Fauvel M. Chalk 14 7 0 18 Oct 2021
On out-of-distribution detection with Bayesian neural networks Francesco DÁngelo Christian Henning BDL UQCV 21 6 0 12 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 45 48 0 06 Oct 2021
Prediction of Energy Consumption for Variable Customer Portfolios Including Aleatoric Uncertainty Estimation Oliver Mey André Schneider Olaf Enge-Rosenblatt Yesnier Bravo P. Stenzel 15 6 0 01 Oct 2021
Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction Tareen Dawood C. L. P. Chen R. Andlauer B. Sidhu B. Ruijsink ... Vishal S. Mehta C. Rinaldi Esther Puyol-Antón Reza Razavi A. King 15 2 0 22 Sep 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseo Lee Jianxiang Feng Matthias Humt M. Müller Rudolph Triebel UQCV 48 21 0 20 Sep 2021
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression Masaki Morimoto Kai Fukami R. Maulik Ricardo Vinuesa K. Fukagata UQCV 22 30 0 16 Sep 2021
Uncertainty-Aware Machine Translation Evaluation T. Glushkova Chrysoula Zerva Ricardo Rei André F.T. Martins UQLM 22 42 0 13 Sep 2021
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation Zhaoshuo Li Nathan G. Drenkow Hao Ding Andy S Ding A. Lu Francis X. Creighton Russell H. Taylor Mathias Unberath MDE 22 8 0 13 Sep 2021
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning Preethi Lahoti Krishna P. Gummadi G. Weikum 34 3 0 09 Sep 2021
On the effects of biased quantum random numbers on the initialization of artificial neural networks R. Heese Moritz Wolter Sascha Mucke L. Franken Nico Piatkowski 16 2 0 30 Aug 2021
Deep few-shot learning for bi-temporal building change detection M. Khoshboresh-Masouleh R. Shah-Hosseini 4 4 0 25 Aug 2021
Monte Carlo DropBlock for Modelling Uncertainty in Object Detection K. Deepshikha Sai Harsha Yelleni P. K. Srijith C.Krishna Mohan BDL UQCV 29 87 0 08 Aug 2021
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Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling N. Khanzhina Alexey Lapenok Andrey Filchenkov UQCV 23 3 0 02 Aug 2021
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? Balázs Kégl Gabriel Hurtado Albert Thomas 9 12 0 24 Jul 2021
Confidence Aware Neural Networks for Skin Cancer Detection Donya Khaledyan AmirReza Tajally A. Sarkhosh Afshar Shamsi Jokandan Hamzeh Asgharnezhad Abbas Khosravi S. Nahavandi 6 10 0 19 Jul 2021
Attribution of Predictive Uncertainties in Classification Models Iker Perez Piotr Skalski Alec E. Barns-Graham Jason Wong David Sutton UQCV 19 5 0 19 Jul 2021