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Conformal prediction (CP) is a method for constructing a prediction interval around the output of a fitted model, whose validity does not rely on the model being correct--the CP interval offers a coverage guarantee that is distribution-free, but relies on the training data being drawn from the same distribution as the test data.
Learning by transduction
Alex Gammerman, Volodya Vovk, and Vladimir Vapnik · 1998
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Transduction with confidence and credibility
Craig Saunders, Alexander Gammerman, and Volodya Vovk · 1999
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Inductive confidence machines for regression
Harris Papadopoulos, Kostas Proedrou, Vladimir Vovk, and Alex Gammerman · 2002
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Algorithmic learning in a random world , volume 29
Vladimir Vovk, Alexander Gammerman, and Glenn Shafer · 2005
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Inductive conformal prediction: Theory and application to neural networks
Harris Papadopoulos · 2008
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Conservative hypothesis tests and confidence intervals using importance sampling
Matthew T Harrison · 2012
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Distribution-free predictive inference for regression
Jing Lei, Max G’Sell, Alessandro Rinaldo, Ryan J Tibshirani, and Larry Wasserman · 2018
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Conformalized quantile regression
Yaniv Romano, Evan Patterson, and Emmanuel Candès · 2019
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Conformal prediction under covariate shift
Ryan J Tibshirani, Rina Foygel Barber, Emmanuel Candès, and Aaditya Ramdas · 2019
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Distribution-free binary classification: prediction sets, confidence intervals and calibration
Chirag Gupta, Aleksandr Podkopaev, and Aaditya Ramdas · 2020
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Conformal inference of counterfactuals and individual treatment effects
Lihua Lei and Emmanuel J Candès · 2021
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Distribution-free prediction sets for two-layer hierarchical models
Robin Dunn, Larry Wasserman, and Aaditya Ramdas · 2022
Cited alongside, same era.
Conformal prediction under feedback covariate shift for biomolecular design
Clara Fannjiang, Stephen Bates, Anastasios N Angelopoulos, Jennifer Listgarten, and Michael I Jordan · 2022
Cited alongside, same era.
Doubly robust calibration of prediction sets under covariate shift
Yachong Yang, Arun Kumar Kuchibhotla, and Eric Tchetgen Tchetgen · 2022
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Conformal sensitivity analysis for individual treatment effects
Mingzhang Yin, Claudia Shi, Yixin Wang, and David M Blei · 2022
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Conformalized survival analysis
Emmanuel Candès, Lihua Lei, and Zhimei Ren · 2023
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Class-conditional conformal prediction with many classes
Tiffany Ding, Anastasios N Angelopoulos, Stephen Bates, Michael I Jordan, and Ryan J Tibshirani · 2023
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Conformal prediction with conditional guarantees
Isaac Gibbs, John J Cherian, and Emmanuel J Candès · 2023
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Yu Gui, Rohan Hore, Zhimei Ren, and Rina Foygel Barber · 2022
Cited alongside, same era.
Batch multivalid conformal prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam, and Aaron Roth · 2022
Cited alongside, same era.
Sensitivity analysis of individual treatment effects: a robust conformal inference approach
Ying Jin, Zhimei Ren, and Emmanuel J Candès · 2023
Later among the works it cites.
Distribution-free inference with hierarchical data
Yonghoon Lee, Rina Foygel Barber, and Rebecca Willett · 2023
Later among the works it cites.