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Split conformal prediction (CP) is arguably the most popular CP method for uncertainty quantification, enjoying both academic interest and widespread deployment.
Conformal prediction: A gentle introduction
Anastasios N. Angelopoulos and Stephen Bates · 1935
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On the density of families of sets
Norbert Sauer · 1972
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Mixing properties of ARMA processes
Abdelkader Mokkadem · 1988
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Rates of convergence for empirical processes of stationary mixing sequences
Bin Yu · 1994
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Mixing and moment properties of various GARCH and stochastic volatility models
Marine Carrasco and Xiaohong Chen · 2002
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Inductive confidence machines for regression
Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, and Alexander Gammerman · 2002
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Cyclostationarity: Half a century of research
William A. Gardner; Antonio Napolitano; Luigi Paura · 2005
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Algorithmic Learning in a Random World
Vladimir Vovk, Alex Gammerman, and Glenn Shafer · 2005
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Rademacher complexity bounds for non-i.i.d. processes
Mehryar Mohri and Afshin Rostamizadeh · 2008
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A tutorial on conformal prediction
Glenn Shafer and Vladimir Vovk · 2008
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Stability bounds for stationary φ \varphi -mixing and β \beta -mixing processes
Mehryar Mohri and Afshin Rostamizadeh · 2010
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NOAA’s 1981–2010 US climate normals: an overview
Anthony Arguez, Imke Durre, Scott Applequist, Russell S Vose, Michael F Squires, Xungang Yin, Richard R Heim, and Timothy W Owen · 2012
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Mixing: properties and examples , volume 85
Paul Doukhan · 2012
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Estimating beta-mixing coefficients via histograms
Daniel J. McDonald, Cosma Rohilla Shalizi, and Mark Schervish · 2015
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Generalization bounds for non-stationary mixing processes
Vitaly Kuznetsov and Mehryar Mohri · 2017
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Distribution-free predictive inference for regression
Jing Lei, Max G’Sell, Alessandro Rinaldo, Ryan J. Tibshirani, and Larry Wasserman · 2017
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Exact and robust conformal inference methods for predictive machine learning with dependent data
Victor Chernozhukov, Kaspar Wüthrich, and Yinchu Zhu · 2018
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Foundations of Machine Learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
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Yotam Hechtlinger, Barnabas Poczos, and Larry Wasserman · 2019
Conformal prediction interval for dynamic time-series
Chen Xu and Yao Xie · 2021
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Risk control for online learning models
Shai Feldman, Liran Ringel, Stephen Bates, and Yaniv Romano · 2022
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https://www.histdata.com/ , Retrieved on 2022-01-27
HistData, 2022 · 2022
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Ensemble conformalized quantile regression for probabilistic time series forecasting
Vilde Jensen, Filippo Maria Bianchi, and Stian Norman Anfinsen · 2022
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HistData API
Philippe Rémy · 2022
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Mapie: an open-source library for distribution-free uncertainty quantification, 2022
Vianney Taquet, Vincent Blot, Thomas Morzadec, Louis Lacombe, and Nicolas Brunel · 2022
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Improving subseasonal forecasting in the western US with machine learning
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Conformalized quantile regression
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Uncertainty sets for image classifiers using conformal prediction
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Distribution-free, risk-controlling prediction sets
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Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction
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Distributional conformal prediction
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Adaptive conformal predictions for time series
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Conformal prediction beyond exchangeability
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http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP/.CPC/.temperature/.daily/ , Retrieved on 2023-03-08
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Conformal prediction for time series
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Hoeffding and bernstein inequalities for weighted sums of exchangeable random variables
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Conformal inference for online prediction with arbitrary distribution shifts
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The limits of distribution-free conditional predictive inference
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