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With increasing deployment of machine learning systems in various real-world tasks, there is a greater need for accurate quantification of predictive uncertainty.
A new vector partition of the probability score
Allan H Murphy · 1973
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Estimating the mean and variance of the target probability distribution
David A Nix and Andreas S Weigend · 1994
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Efficient global optimization of expensive black-box functions
Donald R Jones, Matthias Schonlau, and William J Welch · 1998
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Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting and Adrian E Raftery · 2007
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Probabilistic forecasts, calibration and sharpness
Tilmann Gneiting, Fadoua Balabdaoui, and Adrian E Raftery · 2007
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Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas · 2015
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Inherent trade-offs in the fair determination of risk scores
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2016
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Probabilistic forecasting of electricity spot prices using factor quantile regression averaging
Katarzyna Maciejowska, Jakub Nowotarski, and Rafał Weron · 2016
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
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Calibration for the (computationally-identifiable) masses
Ursula Hébert-Johnson, Michael P Kim, Omer Reingold, and Guy N Rothblum · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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When a computer program keeps you in jail: How computers are harming criminal justice
Rebecca Wexler · 2017
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On the comparison of interval forecasts
Ross Askanazi, Francis X Diebold, Frank Schorfheide, and Minchul Shin · 2018
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Accurate uncertainties for deep learning using calibrated regression
Volodymyr Kuleshov, Nathan Fenner, and Stefano Ermon · 2018
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Uncertainty in neural networks: Approximately bayesian ensembling
Tim Pearce, Felix Leibfried, Alexandra Brintrup, Mohamed Zaki, and Andy Neely · 2018
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VE Bowman, DS Silk, U Dalrymple, and DC Woods · 2020
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Beyond pinball loss: Quantile methods for calibrated uncertainty quantification
Youngseog Chung, Willie Neiswanger, Ian Char, and Jeff Schneider · 2020
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Calibrated reliable regression using maximum mean discrepancy
Peng Cui, Wenbo Hu, and Jun Zhu · 2020
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Robustness Metrics, 2020
Josip Djolonga, Frances Hubis, Matthias Minderer, Zachary Nado, Jeremy Nixon, Rob Romijnders, Dustin Tran, and Mario Lucic · 2020
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Fast calibrated additive quantile regression
Matteo Fasiolo, Simon N Wood, Margaux Zaffran, Raphaël Nedellec, and Yannig Goude · 2020
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Nicki S Detlefsen, Martin Jørgensen, and Søren Hauberg · 2019
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Calibrated model-based deep reinforcement learning
Ali Malik, Volodymyr Kuleshov, Jiaming Song, Danny Nemer, Harlan Seymour, and Stefano Ermon · 2019
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin · 2019
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Distribution calibration for regression
Hao Song, Tom Diethe, Meelis Kull, and Peter Flach · 2019
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Single-model uncertainties for deep learning
Natasa Tagasovska and David Lopez-Paz · 2019
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Methods for comparing uncertainty quantifications for material property predictions
Kevin Tran, Willie Neiswanger, Junwoong Yoon, Qingyang Zhang, Eric Xing, and Zachary W Ulissi · 2020
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Mopo: Model-based offline policy optimization
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, and Tengyu Ma · 2020
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Individual calibration with randomized forecasting
Shengjia Zhao, Tengyu Ma, and Stefano Ermon · 2020
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Evaluating epidemic forecasts in an interval format
Johannes Bracher, Evan L Ray, Tilmann Gneiting, and Nicholas G Reich · 2021
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Uncertainty Baselines: Benchmarks for uncertainty & robustness in deep learning
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, and Dustin Tran · 2021
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