# Multi Split Conformal Prediction

arXiv: https://arxiv.org/abs/2103.00627 · HTML: https://mlsanity.com/paper/2103.00627/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2021.

## Built on by (most cited first, 21 of 21)

- [Conformal Off-policy Prediction](https://mlsanity.com/paper/2206.06711/) (2022)
- [Conformal Prediction for Network-Assisted Regression](https://mlsanity.com/paper/2302.10095/) (2023)
- [Conformal online model aggregation](https://mlsanity.com/paper/2403.15527/) (2024)
- [Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction](https://mlsanity.com/paper/2401.06421/) (2024)
- [COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits](https://mlsanity.com/paper/2403.11348/) (2024)
- [Certifiably Byzantine-Robust Federated Conformal Prediction](https://mlsanity.com/paper/2406.01960/) (2024)
- [Conformal Prediction Bands for Two-Dimensional Functional Time Series](https://mlsanity.com/paper/2207.13656/) (2022)
- [Improving the statistical efficiency of cross-conformal prediction](https://mlsanity.com/paper/2503.01495/) (2025)
- [Uncertainty quantification in metric spaces](https://mlsanity.com/paper/2405.05110/) (2024)
- [Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning](https://mlsanity.com/paper/2410.09878/) (2024)
- [Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series](https://mlsanity.com/paper/2605.30292/) (2026)
- [A novel Deep Learning approach for one-step Conformal Prediction approximation](https://mlsanity.com/paper/2207.12377/) (2022)
- [Leave-One-Out Stable Conformal Prediction](https://mlsanity.com/paper/2504.12189/) (2025)
- [Uncertainty Quantification With Multiple Sources](https://mlsanity.com/paper/2405.06479/) (2024)
- [Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces](https://mlsanity.com/paper/2507.15741/) (2025)
- [Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation](https://mlsanity.com/paper/2510.26026/) (2025)
- [A Confidence Machine for Sparse High-Order Interaction Model](https://mlsanity.com/paper/2205.14317/) (2022)
- [Data-light Uncertainty Set Merging with Admissibility](https://mlsanity.com/paper/2410.12201/) (2024)
- [Improving Coverage in Combined Prediction Sets with Weighted p-values](https://mlsanity.com/paper/2505.11785/) (2025)
- [Set-Preserving Calibration from Conformal P-Values to E-Values](https://mlsanity.com/paper/2606.03600/) (2026)
- [Rolling Conformal Prediction in Sequential Model Training](https://mlsanity.com/paper/2609.26951/) (2026)

## Abstract (arXiv)

Split conformal prediction is a computationally efficient method for performing distribution-free predictive inference in regression. It involves, however, a one-time random split of the data, and the result depends on the particular split. To address this problem, we propose multi split conformal prediction, a simple method based on Markov's inequality to aggregate single split conformal prediction intervals across multiple splits.