mlsanityData to 7 Oct 2026

Nested conformal prediction and quantile out-of-bag ensemble methods

arXiv 1910.10562 ↗First posted 23 Oct 2019stat.ME cs.AI math.STcited by 88

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Abstract (arXiv)

Conformal prediction is a popular tool for providing valid prediction sets for classification and regression problems, without relying on any distributional assumptions on the data. While the traditional description of conformal prediction starts with a nonconformity score, we provide an alternate (but equivalent) view that starts with a sequence of nested sets and calibrates them to find a valid prediction set. The nested framework subsumes all nonconformity scores, including recent proposals based on quantile regression and density estimation. While these ideas were originally derived based on sample splitting, our framework seamlessly extends them to other aggregation schemes like cross-conformal, jackknife+ and out-of-bag methods. We use the framework to derive a new algorithm (QOOB, pronounced cube) that combines four ideas: quantile regression, cross-conformalization, ensemble methods and out-of-bag predictions. We develop a computationally efficient implementation of cross-conformal, that is also used by QOOB. In a detailed numerical investigation, QOOB performs either the best or close to the best on all simulated and real datasets. Code for QOOB is available at https://github.com/aigen/QOOB.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Oct 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 14; 2023: 16; 2024: 11; 2025: 26; 2026: 8.

88 papers.

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  1. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 777
  2. 2021Distribution-Free, Risk-Controlling Prediction Setscited by 278
  3. 2021Testing for Outliers with Conformal p-valuescited by 133
  4. 2024Language Models with Conformal Factuality Guaranteescited by 128
  5. 2021Distribution-free uncertainty quantification for classification under label shiftcited by 99
  6. 2021Conformal Prediction using Conditional Histogramscited by 77
  7. 2023Improved Online Conformal Prediction via Strongly Adaptive Online Learningcited by 76
  8. 2022Sequential Predictive Conformal Inference for Time Seriescited by 71
  9. 2021Conformalized Survival Analysiscited by 53
  10. 2023How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Controlcited by 50
  11. 2021Calibrated Multiple-Output Quantile Regression with Representation Learningcited by 49
  12. 2021Improving Conditional Coverage via Orthogonal Quantile Regressioncited by 48
38 more
  1. 2021PAC Prediction Sets Under Covariate Shiftcited by 42
  2. 2022Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Setscited by 38
  3. 2025Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agentscited by 37
  4. 2022Conformal Prediction Sets with Limited False Positivescited by 28
  5. 2023Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problemscited by 28
  6. 2023One-Shot Federated Conformal Predictioncited by 26
  7. 2022Efficient and Differentiable Conformal Prediction with General Function Classescited by 25
  8. 2023Probabilistically robust conformal predictioncited by 25
  9. 2023Conformal Prediction with Missing Valuescited by 24
  10. 2021Selective Ensembles for Consistent Predictionscited by 23
  11. 2024Probabilistic Conformal Prediction with Approximate Conditional Validitycited by 23
  12. 2023Transductive conformal inference with adaptive scorescited by 21
  13. 2025Conformal Linguistic Calibration: Trading-off between Factuality and Specificitycited by 20
  14. 2022Integrative conformal p-values for powerful out-of-distribution testing with labeled outlierscited by 19
  15. 2024Conformal Semantic Image Segmentation: Post-hoc Quantification of Predictive Uncertaintycited by 19
  16. 2023Integrating Uncertainty Awareness into Conformalized Quantile Regressioncited by 17
  17. 2021Learning Prediction Intervals for Regression: Generalization and Calibrationcited by 16
  18. 2023Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysiscited by 16
  19. 2023Derandomized Novelty Detection with FDR Control via Conformal E-valuescited by 15
  20. 2022Conformal Off-policy Predictioncited by 14
  21. 2022Predictive Inference with Weak Supervisioncited by 13
  22. 2024Multi-group Uncertainty Quantification for Long-form Text Generationcited by 13
  23. 2025Conformal Prediction for Image Segmentation Using Morphological Prediction Setscited by 13
  24. 2024Bellman Conformal Inference: Calibrating Prediction Intervals For Time Seriescited by 12
  25. 2024Conformal Thresholded Intervals for Efficient Regressioncited by 11
  26. 2021Exact Optimization of Conformal Predictors via Incremental and Decremental Learningcited by 10
  27. 2022Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queriescited by 10
  28. 2025Volume Optimality in Conformal Prediction with Structured Prediction Setscited by 9
  29. 2023Conformalized Unconditional Quantile Regressioncited by 8
  30. 2024Cross-Validation Conformal Risk Controlcited by 8
  31. 2025Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factualitycited by 8
  32. 2024Robust Conformal Prediction Using Privileged Informationcited by 7
  33. 2025Guaranteed prediction sets for functional surrogate modelscited by 7
  34. 2025Parametric Scaling Law of Tuning Bias in Conformal Predictioncited by 7
  35. 2024Selecting informative conformal prediction sets with false coverage rate controlcited by 6
  36. 2025Volume-Sorted Prediction Set: Efficient Conformal Prediction for Multi-Target Regressioncited by 6
  37. 2025Document Summarization with Conformal Importance Guaranteescited by 6
  38. 2025Human-AI Collaborative Uncertainty Quantificationcited by 6

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