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There is a significant need for principled uncertainty reasoning in machine learning systems as they are increasingly deployed in safety-critical domains.
A Parsimonious Tour of Bayesian Model Uncertainty
Mattei, P.-A. 2020 · 1902
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Estimating the mean and variance of the target probability distribution
Nix, D. A.; and Weigend, A. S. 1994 · 1994
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Aleatory and epistemic uncertainty in probability elicitation with an example from hazardous waste management
Hora, S. C. 1996 · 1996
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Bayesian Learning for Neural Networks
Neal, R. M. 1996 · 1996
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Aleatory or epistemic? Does it matter?
Kiureghian, A. D.; and Ditlevsen, O. 2009 · 2009
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Can You Trust Your Model’s Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Ovadia, Y.; Fertig, E.; Ren, J.; Nado, Z.; Sculley, D.; Nowozin, S.; Dillon, J. V.; Lakshminarayanan, B.; and Snoek, J. 2010 · 2010
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Bayesian learning via stochastic gradient langevin dynamics
Welling, M.; and Teh, Y. W. 2011 · 2011
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Indoor Segmentation and Support Inference from RGBD Images
Silberman, N.; Hoiem, D.; Kohli, P.; and Fergus, R. 2012 · 2012
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Bayesian Data Analysis
Gelman, A.; Carlin, J.; Stern, H.; Dunson, D.; Vehtari, A.; and Rubin, D. 2013 · 2013
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Speech Recognition with Deep Recurrent Neural Networks
Graves, A.; Mohamed, A.; and Hinton, G. 2013 · 2013
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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Gal, Y.; and Ghahramani, Z. 2016 · 2016
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Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification
Li, C.; Stevens, A.; Chen, C.; Pu, Y.; Gan, Z.; and Carin, L. 2016 · 2016
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Deep Kernel Learning
Wilson, A. G.; Hu, Z.; Salakhutdinov, R.; and Xing, E. P. 2016 · 2016
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On Calibration of Modern Neural Networks
Guo, C.; Pleiss, G.; Sun, Y.; and Weinberger, K. Q. 2017 · 2017
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What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Kendall, A.; and Gal, Y. 2017 · 2017
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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Lakshminarayanan, B.; Pritzel, A.; and Blundell, C. 2017 · 2017
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Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Garipov, T.; Izmailov, P.; Podoprikhin, D.; Vetrov, D.; and Wilson, A. G. 2018 · 2018
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The ApolloScape Dataset for Autonomous Driving
Huang, X.; Cheng, X.; Geng, Q.; Cao, B.; Zhou, D.; Wang, P.; Lin, Y.; and Yang, R. 2018 · 2018
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Accurate Uncertainties for Deep Learning Using Calibrated Regression
Kuleshov, V.; Fenner, N.; and Ermon, S. 2018 · 2018
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Predictive Uncertainty Estimation via Prior Networks
Malinin, A.; and Gales, M. 2018 · 2018
Towards calibrated and scalable uncertainty representations for Neural Networks
Seedat, N.; and Kanan, C. 2020 · 2020
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Classifier-agnostic saliency map extraction
Zolna, K.; Geras, K. J.; and Cho, K. 2020 · 2020
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Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning
Cai, P.; Wang, H.; Huang, H.; Liu, Y.; and Liu, M. 2021 · 2021
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Neural Machine Translation for Harmonized System Codes Prediction
Chen, X.; Bromuri, S.; and van Eekelen, M. 2021 · 2021
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Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
Hüllermeier, E.; and Waegeman, W. 2021 · 2021
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Efficient and Robust LiDAR-Based End-to-End Navigation
Liu, Z.; Amini, A.; Zhu, S.; Karaman, S.; Han, S.; and Rus, D. 2021 · 2021
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Cited alongside, same era.
Sampling-based Bayesian Inference with gradient uncertainty
Park, C.; Kim, J. M.; Ha, S. H.; and Lee, J. 2018 · 2018
Cited alongside, same era.
Evidential Deep Learning to Quantify Classification Uncertainty
Sensoy, M.; Kaplan, L.; and Kandemir, M. 2018 · 2018
Cited alongside, same era.
Gradient conjugate priors and multi-layer Neural Networks
Gurevich, P.; and Stuke, H. 2019 · 2019
Cited alongside, same era.
Noise Contrastive Priors for Functional Uncertainty
Hafner, D.; Tran, D.; Lillicrap, T.; Irpan, A.; and Davidson, J. 2019 · 2019
Cited alongside, same era.
Subspace Inference for Bayesian Deep Learning
Izmailov, P.; Maddox, W. J.; Kirichenko, P.; Garipov, T.; Vetrov, D. P.; and Wilson, A. G. 2019 · 2019
Cited alongside, same era.
A Simple Baseline for Bayesian Uncertainty in Deep Learning
Maddox, W.; Garipov, T.; Izmailov, P.; Vetrov, D.; and Wilson, A. G. 2019 · 2019
Cited alongside, same era.
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Multivariate Deep Evidential Regression
Meinert, N.; and Lavin, A. 2021 · 2021
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Evidential Deep Learning for Guided Molecular Property Prediction and Discovery
Soleimany, A. P.; Amini, A.; Goldman, S.; Rus, D.; Bhatia, S. N.; and Coley, C. W. 2021 · 2021
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Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation
Bengs, V.; Hüllermeier, E.; and Waegeman, W. 2022 · 2022
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Hüllermeier, E. 2022 · 2022
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3D High-Quality Magnetic Resonance Image Restoration in Clinics Using Deep Learning
Li, H.; and Liu, J. 2022 · 2022
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Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation
Petek, K.; Sirohi, K.; Büscher, D.; and Burgard, W. 2022 · 2022
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Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies
Singh, S. K.; Fowdur, J. S.; Gawlikowski, J.; and Medina, D. 2022 · 2022
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