% INTRODUCTION
@inproceedings{widmann19-kce,
 author = {Widmann, David and Lindsten, Fredrik and Zachariah, Dave},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Calibration tests in multi-class classification: A unifying framework},
 url = {https://proceedings.neurips.cc/paper/2019/file/1c336b8080f82bcc2cd2499b4c57261d-Paper.pdf},
 volume = {32},
 year = {2019}
}

@article{compas2016,
title={COMPAS Risk Scales: Demonstrating Accuracy Equity and Predictive Parity},
author={Dieterich, William and Mendoza, Christina and Brennan, Tim},
year={2016},
publisher={Northpointe},
}

@article{khan2001classification,
  title={Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks},
  author={Khan, Javed and Wei, Jun S and Ringner, Markus and Saal, Lao H and Ladanyi, Marc and Westermann, Frank and Berthold, Frank and Schwab, Manfred and Antonescu, Cristina R and Peterson, Carsten and others},
  journal={Nature medicine},
  volume={7},
  number={6},
  pages={673},
  year={2001},
  publisher={Nature Publishing Group}
}

@article{Chen2018CalibrationOM,
  title={Calibration of medical diagnostic classifier scores to the probability of disease},
  author={Weijie Chen and Berkman Sahiner and Frank W. Samuelson and Aria Pezeshk and Nicholas A. Petrick},
  journal={Statistical methods in medical research},
  year={2018},
  volume={27},
  pages={1394 - 1409}
}

@inproceedings{dwork2012fairness,
author = {Dwork, Cynthia and Hardt, Moritz and Pitassi, Toniann and Reingold, Omer and Zemel, Richard},
title = {Fairness through Awareness},
year = {2012},
isbn = {9781450311151},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
doi = {10.1145/2090236.2090255},
booktitle = {Proceedings of the 3rd Innovations in Theoretical Computer Science Conference},
pages = {214–226},
numpages = {13},
location = {Cambridge, Massachusetts},
series = {ITCS '12}
}

@article{stuart2010matching,
    title={Matching methods for causal inference: A review and a look forward},
    author = {Elizabeth A. Stuart},
    journal={Statistical science : a review journal of the Institute of Mathematical Statistics},
    volume={25},
    number={1},
    pages={1--21},
    doi={10.1214/09-STS313},
    year={2010}
}

@article{berestycki2002asymptotics,
  title={Asymptotics and calibration of local volatility models},
  author={Berestycki, Henri and Busca, J{\'e}r{\^o}me and Florent, Igor},
  journal={Quantitative finance},
  volume={2},
  number={1},
  pages={61--69},
  year={2002},
  publisher={Taylor \& Francis}
}

@inproceedings{kendall2017uncertainties,
  title={What uncertainties do we need in bayesian deep learning for computer vision?},
  author={Kendall, Alex and Gal, Yarin},
  booktitle={Advances in neural information processing systems},
  pages={5574--5584},
  year={2017}
}

@inproceedings{Yang2018RealtoVirtualDU,
  title={Real-to-Virtual Domain Unification for End-to-End Autonomous Driving},
  author={Luona Yang and Xiaodan Liang and Tairui Wang and Eric P. Xing},
  booktitle={ECCV},
  year={2018}
}

% BACKGROUND

@article{brier1950verification,
  title={Verification of forecasts expressed in terms of probability},
  author={Brier, Glenn W},
  journal={Monthly weather review},
  volume={78},
  number={1},
  pages={1--3},
  year={1950}
}

@article{gneiting2007probabilistic,
  title={Probabilistic forecasts, calibration and sharpness},
  author={Gneiting, Tilmann and Balabdaoui, Fadoua and Raftery, Adrian E},
  journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
  volume={69},
  number={2},
  pages={243--268},
  year={2007},
  publisher={Wiley Online Library}
}

@book{cesa2006prediction,
  title={Prediction, learning, and games},
  author={Cesa-Bianchi, Nicolo and Lugosi, Gabor},
  year={2006},
  publisher={Cambridge university press}
}

@inproceedings{Zhao2020IndividualCW,
  title={Individual Calibration with Randomized Forecasting},
  author={Shengjia Zhao and Tengyu Ma and S. Ermon},
  booktitle={ICML},
  year={2020}
}

@misc{zhao2021calibrating,
      title={Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration}, 
      author={Shengjia Zhao and Michael P. Kim and Roshni Sahoo and Tengyu Ma and Stefano Ermon},
      year={2021},
      eprint={2107.05719},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}

@InProceedings{kumar18a-mmce,
 title = {Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings},
 author = {Kumar, Aviral and Sarawagi, Sunita and Jain, Ujjwal},
 booktitle = {Proceedings of the 35th International Conference on Machine Learning},
 pages = {2805--2814},
 year = {2018},
 editor = {Jennifer Dy and Andreas Krause},
 volume = {80},
 series = {Proceedings of Machine Learning Research}, 
 address = {Stockholmsmässan, Stockholm Sweden},
 month = {10--15 Jul},
 publisher = {PMLR},
 url = {http://proceedings.mlr.press/v80/kumar18a.html}
}

@inproceedings{pleiss17-fairness,
 author = {Pleiss, Geoff and Raghavan, Manish and Wu, Felix and Kleinberg, Jon and Weinberger, Kilian Q},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
 pages = {5680--5689},
 publisher = {Curran Associates, Inc.},
 title = {On Fairness and Calibration},
 url = {https://proceedings.neurips.cc/paper/2017/file/b8b9c74ac526fffbeb2d39ab038d1cd7-Paper.pdf},
 volume = {30},
 year = {2017}
}

@INPROCEEDINGS{zadrozny01-hb,
 author = {Bianca Zadrozny and Charles Elkan},
 title = {Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers},
 booktitle = {In Proceedings of the Eighteenth International Conference on Machine Learning},
 year = {2001},
 pages = {609--616},
 publisher = {Morgan Kaufmann}
}

@INPROCEEDINGS{platt99,
    author = {John C. Platt},
    title = {Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods},
    booktitle = {Advances in Large Margin Classifiers},
    year = {1999},
    pages = {61--74},
    publisher = {MIT Press}
}

@InProceedings{guo17-ts,
 title = {On Calibration of Modern Neural Networks},
 author = {Chuan Guo and Geoff Pleiss and Yu Sun and Kilian Q. Weinberger},
 booktitle = {Proceedings of the 34th International Conference on Machine Learning},
 pages = {1321--1330},
 year = {2017},
 editor = {Doina Precup and Yee Whye Teh},
 volume = {70},
 series = {Proceedings of Machine Learning Research},
 address = {International Convention Centre, Sydney, Australia},
 month = {06--11 Aug},
 publisher = {PMLR},
 url = {http://proceedings.mlr.press/v70/guo17a.html}
}

@misc{kleinberg16-groupcal,
  author    = {Jon M. Kleinberg and
               Sendhil Mullainathan and
               Manish Raghavan},
  title     = {Inherent Trade-Offs in the Fair Determination of Risk Scores},
  year      = {2016},
  url       = {http://arxiv.org/abs/1609.05807},
  archivePrefix = {arXiv},
  eprint    = {1609.05807},
}

@misc{hebert-johnson17-groupcal,
  author    = {{\'{U}}rsula H{\'{e}}bert{-}Johnson and
               Michael P. Kim and
               Omer Reingold and
               Guy N. Rothblum},
  title     = {Calibration for the (Computationally-Identifiable) Masses},
  year      = {2017},
  url       = {http://arxiv.org/abs/1711.08513},
  archivePrefix = {arXiv},
  eprint    = {1711.08513},
}

@misc{ding20-lts,
      title={Local Temperature Scaling for Probability Calibration}, 
      author={Zhipeng Ding and Xu Han and Peirong Liu and Marc Niethammer},
      year={2020},
      eprint={2008.05105},
      archivePrefix={arXiv},
      url={http://arxiv.org/abs/2008.05105},
}

@misc{huh16makes,
      title={What makes ImageNet good for transfer learning?}, 
      author={Minyoung Huh and Pulkit Agrawal and Alexei A. Efros},
      year={2016},
      eprint={1608.08614},
      archivePrefix={arXiv},
      url={http://arxiv.org/abs/1608.08614}
}

@inproceedings{liu2015faceattributes,
 title = {Deep Learning Face Attributes in the Wild},
 author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
 booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
 month = {December},
 year = {2015} 
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle={2009 IEEE conference on computer vision and pattern recognition},
  pages={248--255},
  year={2009},
  organization={Ieee}
}

@misc{
 bai2021improved,
 title={Improved Uncertainty Post-Calibration via Rank Preserving Transforms},
 author={Yu Bai and Tengyu Ma and Huan Wang and Caiming Xiong},
 year={2021},
 url={https://openreview.net/forum?id=jsM6yvqiT0W}
}

@misc{dua-uci ,
author = "Dua, Dheeru and Graff, Casey",
year = "2017",
title = "{UCI} Machine Learning Repository",
url = "http://archive.ics.uci.edu/ml",
institution = "University of California, Irvine, School of Information and Computer Sciences"
}


@inproceedings{kingma15-adam,
  author={Diederik P. Kingma and Jimmy Ba},
  title={Adam: A Method for Stochastic Optimization},
  year={2015},
  url={http://arxiv.org/abs/1412.6980},
  booktitle={ICLR},
}

@inproceedings{li20-sentence,
    title = "On the Sentence Embeddings from Pre-trained Language Models",
    author = "Li, Bohan  and
      Zhou, Hao  and
      He, Junxian  and
      Wang, Mingxuan  and
      Yang, Yiming  and
      Li, Lei",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = Nov,
    year = "2020",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.733",
    doi = "10.18653/v1/2020.emnlp-main.733",
    pages = "9119--9130"
}

@InProceedings{chen20-simple,
 title = {A Simple Framework for Contrastive Learning of Visual Representations},
 author = {Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
 booktitle = {Proceedings of the 37th International Conference on Machine Learning},
 pages = {1597--1607},
 year = {2020},
 editor = {Hal Daumé III and Aarti Singh},
 volume = {119},
 series = {Proceedings of Machine Learning Research},
 month = {13--18 Jul},
 publisher = {PMLR},
 url = { http://proceedings.mlr.press/v119/chen20j.html }
}


@inproceedings{kull19-dirichlet,
 author = {Kull, Meelis and Perello Nieto, Miquel and K\"{a}ngsepp, Markus and Silva Filho, Telmo and Song, Hao and Flach, Peter},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {12316--12326},
 publisher = {Curran Associates, Inc.},
 title = {Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration},
 url = {https://proceedings.neurips.cc/paper/2019/file/8ca01ea920679a0fe3728441494041b9-Paper.pdf},
 volume = {32},
 year = {2019}
}

@article{Nixon2019MeasuringCI,
  title={Measuring Calibration in Deep Learning},
  author={Jeremy Nixon and Michael W. Dusenberry and Linchuan Zhang and Ghassen Jerfel and Dustin Tran},
  journal={ArXiv},
  year={2019},
  volume={abs/1904.01685}
}

@conference{naeini2015obtaining,
	title = {Obtaining Well Calibrated Probabilities Using Bayesian Binning.},
	booktitle = {AAAI},
	year = {2015},
	pages = {2901{\textendash}2907},
	author = {Mahdi Pakdaman Naeini and Cooper, Gregory F and Hauskrecht, Milos}
}

@conference{zadrozny02-isotonic,
    author = {Bianca Zadrozny and Charles Elkan},
    title = {Transforming Classifier Scores into Accurate Multiclass Probability Estimates},
    year = {2002},
    booktitle={SIGKDD}
}

@article{Malinin2020EnsembleDD,
  title={Ensemble Distribution Distillation},
  author={A. Malinin and Bruno Mlodozeniec and M. Gales},
  journal={ArXiv},
  year={2020},
  volume={abs/1905.00076}
}

@inproceedings{Salimans2016ImprovedTF,
  title={Improved Techniques for Training GANs},
  author={Tim Salimans and Ian J. Goodfellow and Wojciech Zaremba and Vicki Cheung and Alec Radford and Xi Chen},
  booktitle={NIPS},
  year={2016}
}

@article{AlexNet,
  author    = {Alex Krizhevsky},
  title     = {One weird trick for parallelizing convolutional neural networks},
  journal   = {CoRR},
  volume    = {abs/1404.5997},
  year      = {2014},
  url       = {http://arxiv.org/abs/1404.5997},
  archivePrefix = {arXiv},
  eprint    = {1404.5997},
  timestamp = {Mon, 13 Aug 2018 16:48:41 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/Krizhevsky14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{DenseNet,
      title={Densely Connected Convolutional Networks}, 
      author={Gao Huang and Zhuang Liu and Laurens van der Maaten and Kilian Q. Weinberger},
      year={2018},
      eprint={1608.06993},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@article{ResNet,
      title={Deep Residual Learning for Image Recognition}, 
      author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
      year={2015},
      eprint={1512.03385},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@article{zhang2020mixnmatch,
      title={Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning}, 
      author={Jize Zhang and Bhavya Kailkhura and T. Yong-Jin Han},
      year={2020},
      eprint={2003.07329},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@article{gupta2020calibration,
      title={Calibration of Neural Networks using Splines}, 
      author={Kartik Gupta and Amir Rahimi and Thalaiyasingam Ajanthan and Thomas Mensink and Cristian Sminchisescu and Richard Hartley},
      year={2020},
      eprint={2006.12800},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}