mlsanityData to 14 Oct 2026

Flow-based Conformal Prediction for Multi-dimensional Time Series

arXiv 2502.05709 ↗First posted 8 Feb 2025cs.LG stat.MLcited by 5

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Abstract (arXiv)

Time series prediction underpins a broad range of downstream tasks across many scientific domains. Recent advances and increasing adoption of black-box machine learning models for time series prediction highlight the critical need for uncertainty quantification. While conformal prediction has gained attention as a reliable uncertainty quantification method, conformal prediction for time series faces two key challenges: (1) leveraging correlations in observations and non-conformity scores to overcome the exchangeability assumption, and (2) constructing prediction sets for multi-dimensional outcomes. To address these challenges, we propose a novel conformal prediction method for time series using flow with classifier-free guidance. We provide coverage guarantees by establishing exact non-asymptotic marginal coverage and a finite-sample bound on conditional coverage for the proposed method. Evaluations on real-world time series datasets demonstrate that our method constructs significantly smaller prediction sets than existing conformal prediction methods, maintaining target coverage.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 37 of its 64 references that are in the map. First posted on arXiv 8 Feb 2025.

Builds on

37 of 64 references.

References · 37

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25 more
  1. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  2. 2019Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecastingcited by 761
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  13. 2024A Comprehensive Survey of Deep Learning for Time Series Forecasting: Architectural Diversity and Open Challengescited by 47
  14. 2023Conformal Prediction for Time Series with Modern Hopfield Networkscited by 42
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  18. 2022Copula Conformal Prediction for Multi-step Time Series Forecastingcited by 29
  19. 2025Multivariate Conformal Prediction using Optimal Transportcited by 22
  20. 2025Optimal Transport-based Conformal Predictioncited by 20
  21. 2024Kernel-based Optimally Weighted Conformal Time-Series Predictioncited by 15
  22. 2021Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Datacited by 12
  23. 2021Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Marketcited by 7
  24. 2024Transformer Conformal Prediction for Time Seriescited by 7
  25. 2021Solar Radiation Ramping Events Modeling Using Spatio-temporal Point Processescited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Towards Trustworthy Vital Sign Forecasting: Leveraging Uncertainty for Prediction Intervalscited by 2
  2. 2025Interpretable Multivariate Conformal Prediction with Fast Transductive Standardizationcited by 2
  3. 2026DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Predictioncited by 0
  4. 2026SPACE: Sample-cloud Predictive Adaptive Conformal Ellipsoids for Multivariate Time-Series Forecastingcited by 0
  5. 2026SPARC: Single-Pass Scaling for Motion Forecasting with Conformal Bayesian Last Layerscited by 0