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Applications such as weather forecasting and personalized medicine demand models that output calibrated probability estimates---those representative of the true likelihood of a prediction.
Verification of forecasts expressed in terms of probability
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Transforming classifier scores into accurate multiclass probability estimates
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Estimation of entropy and mutual information
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Weather forecasting with ensemble methods
T. Gneiting and A. E. Raftery · 2005
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Probabilistic forecasts, calibration and sharpness
T. Gneiting, F. Balabdaoui, and A. E. Raftery · 2007
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Increasing the reliability of reliability diagrams
J. Bröcker and L. A. Smith · 2007
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A tutorial on conformal prediction
G. Shafer and V. Vovk · 2008
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Reliability, sufficiency, and the decomposition of proper scores
J. Brocker · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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ImageNet: A large-scale hierarchical image database
cifar-vgg
Yonatan Geifman · 2015
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Distribution-free predictive inference for regression
J. Lei, M. G’Sell, A. Rinaldo, R. J. Tibshirani, and L. Wasserman · 2016
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On calibration of modern neural networks
C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger · 2017
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Assessing calibration of prognostic risk scores
C. S. Crowson, E. J. Atkinson, and T. M. Therneau · 2017
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Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration
M. Kull, T. M. S. Filho, and P. Flach · 2017
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The importance of calibration for estimating proportions from annotations
D. Card and N. A. Smith · 2018
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J. Deng, W. Dong, R. Socher, L. Li, K. Li, and L. Fei-Fei · 2009
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Calibration of confidence measures in speech recognition
D. Yu, J. Li, and L. Deng · 2011
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Calibrating predictive model estimates to support personalized medicine
X. Jiang, M. Osl, J. Kim, and L. Ohno-Machado · 2012
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Estimating reliability and resolution of probability forecasts through decomposition of the empirical score
J. Brocker · 2012
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A bias-corrected decomposition of the brier score
C. A. T. Ferro and T. E. Fricker · 2012
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Binary classifier calibration: Non-parametric approach
M. P. Naeini, G. F. Cooper, and M. Hauskrecht · 2014
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Accurate uncertainties for deep learning using calibrated regression
V. Kuleshov, N. Fenner, and S. Ermon · 2018
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Multicalibration: Calibration for the (computationally-identifiable) masses
U. Hebert-Johnson, M. P. Kim, O. Reingold, and G. N. Rothblum · 2018
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Measuring calibration in deep learning
J. V. Nixon, M. W. Dusenberry, L. Zhang, G. Jerfel, and D. Tran · 2019
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Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with dirichlet calibration
M. Kull, M. P. Nieto, M. Kängsepp, T. S. Filho, H. Song, and P. Flach · 2019
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Evaluating model calibration in classification
J. Vaicenavicius, D. Widmann, C. Andersson, F. Lindsten, J. Roll, and T. B. Schön · 2019
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The implicit fairness criterion of unconstrained learning
L. T. Liu, M. Simchowitz, and M. Hardt · 2019
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A calibration metric for risk scores with survival data
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Calibrated model-based deep reinforcement learning
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Calibration tests in multi-class classification: A unifying framework
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Density estimation
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