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Conformal prediction is a powerful framework for distribution-free uncertainty quantification.
Étude Critique de la Notion de Collectif
Jean Ville · 1939
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Stochastic Processes
Joseph L. Doob · 1953
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Random variables with maximum sums
Ludger Rüschendorf · 1982
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Aggregating strategies
Vladimir Vovk · 1990
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Universal portfolios
Thomas M. Cover · 1991
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Probability with Martingales
David Williams · 1991
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Posterior predictive p-values
Xiao-Li Meng · 1994
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Universal portfolios with side information
Thomas M. Cover and Erik Ordentlich · 1996
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The MNIST database of handwritten digits
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Universal portfolio selection
Vladimir Vovk and Christopher Watkins · 1998
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Inductive confidence machines for regression
Harris Papadopoulos, Kostas Proedrou, Vladimir Vovk, and Alexander Gammerman · 2002
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Post-selection inference for e-value based confidence intervals
Ziyu Xu, Ruodu Wang, and Aaditya Ramdas · 2002
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Algorithmic Learning in a Random World
Vladimir Vovk, Alex Gammerman, and Glenn Shafer · 2005
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications
Vineeth Balasubramanian, Shen-Shyang Ho, and Vladimir Vovk · 2014
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EMNIST: Extending MNIST to handwritten letters
Gregory Cohen, Saeed Afshar, Jonathan Tapson, and André van Schaik · 2017
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LEAF: A benchmark for federated settings
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Human uncertainty makes classification more robust
Joshua Peterson, Ruairidh Battleday, Thomas Griffiths, and Olga Russakovsky · 2019
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Conformalized quantile regression
Yaniv Romano, Evan Patterson, and Emmanuel Candès · 2019
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Least ambiguous set-valued classifiers with bounded error levels
Uncertainty quantification over graph with conformalized graph neural networks
Kexin Huang, Ying Jin, Emmanuel Candès, and Jure Leskovec · 2023
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Selection by prediction with conformal p-values
Ying Jin and Emmanuel Candès · 2023
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Batch multivalid conformal prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam, and Aaron Roth · 2023
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Tight concentrations and confidence sequences from the regret of universal portfolio
Francesco Orabona and Kwang-Sung Jun · 2023
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Conformal prediction under ambiguous ground truth
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, and Arnaud Doucet · 2023
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Estimating means of bounded random variables by betting
Ian Waudby-Smith and Aaditya Ramdas · 2023
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Combining p-values via averaging
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Theoretical foundations of conformal prediction
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Enhancing conformal prediction using e-test statistics
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Conformal prediction with conditional guarantees
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Beyond Neyman-Pearson: E-values enable hypothesis testing with a data-driven alpha
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Post-hoc α \alpha hypothesis testing and the post-hoc p-value
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Hypothesis testing with e-values
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On confidence sequences for bounded random processes via universal gambling strategies
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