mlsanityData to 7 Oct 2026

Distributional conformal prediction

arXiv 1909.07889 ↗First posted 17 Sep 2019econ.EM stat.MEcited by 104

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Abstract (arXiv)

We propose a robust method for constructing conditionally valid prediction intervals based on models for conditional distributions such as quantile and distribution regression. Our approach can be applied to important prediction problems including cross-sectional prediction, k-step-ahead forecasts, synthetic controls and counterfactual prediction, and individual treatment effects prediction. Our method exploits the probability integral transform and relies on permuting estimated ranks. Unlike regression residuals, ranks are independent of the predictors, allowing us to construct conditionally valid prediction intervals under heteroskedasticity. We establish approximate conditional validity under consistent estimation and provide approximate unconditional validity under model misspecification, overfitting, and with time series data. We also propose a simple "shape" adjustment of our baseline method that yields optimal prediction intervals.

Key facts. Cited by 104 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 12; 2023: 16; 2024: 23; 2025: 22; 2026: 23.

104 papers.

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  1. 2021Testing for Outliers with Conformal p-valuescited by 133
  2. 2021Conformal Prediction using Conditional Histogramscited by 77
  3. 2022Selection by Prediction with Conformal p-valuescited by 66
  4. 2021Few-shot Conformal Prediction with Auxiliary Taskscited by 53
  5. 2021Conformalized Survival Analysiscited by 53
  6. 2024Conformal Prediction for Natural Language Processing: A Surveycited by 52
  7. 2021Conformal Uncertainty Sets for Robust Optimizationcited by 49
  8. 2021Calibrated Multiple-Output Quantile Regression with Representation Learningcited by 49
  9. 2021Improving Conditional Coverage via Orthogonal Quantile Regressioncited by 48
  10. 2022Probabilistic Conformal Prediction Using Conditional Random Samplescited by 47
  11. 2024Length Optimization in Conformal Predictioncited by 39
  12. 2022Achieving Risk Control in Online Learning Settingscited by 38
38 more
  1. 2023Non-Exchangeable Conformal Risk Controlcited by 29
  2. 2022Copula Conformal Prediction for Multi-step Time Series Forecastingcited by 28
  3. 2023Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problemscited by 28
  4. 2023A Large-Scale Study of Probabilistic Calibration in Neural Network Regressioncited by 26
  5. 2024Conformal Prediction: A Data Perspectivecited by 25
  6. 2025Minimum Volume Conformal Sets for Multivariate Regressioncited by 25
  7. 2024Probabilistic Conformal Prediction with Approximate Conditional Validitycited by 23
  8. 2025Multivariate Conformal Prediction using Optimal Transportcited by 21
  9. 2022Split Localized Conformal Predictioncited by 20
  10. 2022Integrative conformal p-values for powerful out-of-distribution testing with labeled outlierscited by 19
  11. 2025Optimal Transport-based Conformal Predictioncited by 19
  12. 2024Conformal Prediction via Regression-as-Classificationcited by 18
  13. 2023Improving Adaptive Conformal Prediction Using Self-Supervised Learningcited by 17
  14. 2023Integrating Uncertainty Awareness into Conformalized Quantile Regressioncited by 17
  15. 2022Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problemscited by 14
  16. 2023Conformal inference is (almost) free for neural networks trained with early stoppingcited by 14
  17. 2023Conformal Prediction for Network-Assisted Regressioncited by 14
  18. 2024Neural Conditional Probability for Uncertainty Quantificationcited by 14
  19. 2024Regression Trees for Fast and Adaptive Prediction Intervalscited by 11
  20. 2024Weighted Aggregation of Conformity Scores for Classificationcited by 11
  21. 2024Conformal Thresholded Intervals for Efficient Regressioncited by 11
  22. 2022Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queriescited by 10
  23. 2022Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)cited by 9
  24. 2025Epistemic Uncertainty in Conformal Scores: A Unified Approachcited by 9
  25. 2025Volume Optimality in Conformal Prediction with Structured Prediction Setscited by 9
  26. 2025Predictive inference for time series: why is split conformal effective despite temporal dependence?cited by 9
  27. 2023Conformalized Unconditional Quantile Regressioncited by 8
  28. 2023Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confoundingcited by 7
  29. 2024Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effectscited by 7
  30. 2022Uncertainty-aware predictive modeling for fair data-driven decisionscited by 6
  31. 2023Distribution-free risk assessment of regression-based machine learning algorithmscited by 6
  32. 2024Probabilistic Calibration by Design for Neural Network Regressioncited by 6
  33. 2022Improved conformalized quantile regressioncited by 5
  34. 2023Post-selection Inference for Conformal Prediction: Trading off Coverage for Precisioncited by 5
  35. 2023Conformalized Deep Splines for Optimal and Efficient Prediction Setscited by 5
  36. 2024Toward Conditional Distribution Calibration in Survival Predictioncited by 5
  37. 2025Conditional Conformal Risk Adaptationcited by 5
  38. 2025CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inferencecited by 5

50 most cited of 104 All 104 (JSON)