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Conformal Prediction: a Unified Review of Theory and New Challenges

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arxiv 2005.07972 v2 pith:MM3YABZH submitted 2020-05-16 cs.LG econ.EMstat.MEstat.ML

classification cs.LGecon.EMstat.MEstat.ML
keywords conformalpredictiondevelopmentsreviewableadaptationsadvancedassumptions
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In this work we provide a review of basic ideas and novel developments about Conformal Prediction -- an innovative distribution-free, non-parametric forecasting method, based on minimal assumptions -- that is able to yield in a very straightforward way predictions sets that are valid in a statistical sense also in in the finite sample case. The in-depth discussion provided in the paper covers the theoretical underpinnings of Conformal Prediction, and then proceeds to list the more advanced developments and adaptations of the original idea.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum-Enhanced Conformal Methods for Multi-Output Uncertainty: A Holistic Exploration and Experimental Analysis

    quant-ph 2025-01 conditional novelty 3.0 of 10

    A standard conformal prediction wrapper gives near-nominal coverage for simulated two-qubit measurement distributions in four and twelve dimensions.

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