mlsanityData to 14 Oct 2026

CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference

arXiv 2508.17077 ↗First posted 23 Aug 2025stat.ML cs.LGcited by 6

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Abstract (arXiv)

Current experimental scientists have been increasingly relying on simulation-based inference (SBI) to invert complex non-linear models with intractable likelihoods. However, posterior approximations obtained with SBI are often miscalibrated, causing credible regions to undercover true parameters. We develop textttCP4SBI, a model-agnostic conformal calibration framework that constructs credible sets with local Bayesian coverage. Our two proposed variants, namely local calibration via regression trees and CDF-based calibration, enable finite-sample local coverage guarantees for any scoring function, including HPD, symmetric, and quantile-based regions. Experiments on widely used SBI benchmarks demonstrate that our approach improves the quality of uncertainty quantification for neural posterior estimators using both normalizing flows and score-diffusion modeling.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 41 of its 78 references that are in the map. First posted on arXiv 23 Aug 2025.

Builds on

41 of 78 references.

References · 41

  1. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,323
  2. 2019Conformalized Quantile Regressioncited by 629
  3. 2019The frontier of simulation-based inferencecited by 502
  4. 2018Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flowscited by 221
  5. 2019Automatic Posterior Transformation for Likelihood-Free Inferencecited by 219
  6. 2017Flexible statistical inference for mechanistic models of neural dynamicscited by 163
  7. 2021Benchmarking Simulation-Based Inferencecited by 162
  8. 2023Conformal Prediction With Conditional Guaranteescited by 152
  9. 2021Enhancing Computational Fluid Dynamics with Machine Learningcited by 138
  10. 2019Distributional conformal predictioncited by 105
  11. 2023Flow Matching for Scalable Simulation-Based Inferencecited by 101
  12. 2020On Contrastive Learning for Likelihood-free Inferencecited by 98
29 more
  1. 2015Approximating Likelihood Ratios with Calibrated Discriminative Classifierscited by 90
  2. 2020CD-split and HPD-split: efficient conformal regions in high dimensionscited by 76
  3. 2019Flexible distribution-free conditional predictive bands using density estimatorscited by 64
  4. 2015Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Modelscited by 61
  5. 2016Deep Learning in Bioinformaticscited by 48
  6. 2022Compositional Score Modeling for Simulation-based Inferencecited by 48
  7. 2022Probabilistic Conformal Prediction Using Conditional Random Samplescited by 47
  8. 2022Truncated proposals for scalable and hassle-free simulation-based inferencecited by 41
  9. 2021Diagnostics for Conditional Density Models and Bayesian Inference Algorithmscited by 28
  10. 2022Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimationcited by 28
  11. 2024Addressing Misspecification in Simulation-based Inference through Data-driven Calibrationcited by 27
  12. 2025A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regressioncited by 24
  13. 2024sbi reloaded: a toolkit for simulation-based inference workflowscited by 23
  14. 2014High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computationcited by 19
  15. 2021HNPE: Leveraging Global Parameters for Neural Posterior Estimationcited by 19
  16. 2024Diffusion posterior sampling for simulation-based inference in tall data settingscited by 19
  17. 2020Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Settingcited by 18
  18. 2023L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inferencecited by 18
  19. 2025Rectifying Conformity Scores for Better Conditional Coveragecited by 17
  20. 2022Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problemscited by 15
  21. 2024Regression Trees for Fast and Adaptive Prediction Intervalscited by 12
  22. 2021Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inferencecited by 11
  23. 2023Balancing Simulation-based Inference for Conservative Posteriorscited by 10
  24. 2025Epistemic Uncertainty in Conformal Scores: A Unified Approachcited by 9
  25. 2018ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulationscited by 8
  26. 2019Spectral Density-Based and Measure-Preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEscited by 7
  27. 2024Approximate Bayesian Computation with Deep Learning and Conformal predictioncited by 6
  28. 2025On Focusing Statistical Power for Searches and Measurements in Particle Physicscited by 3
  29. 2022Bayesian score calibration for approximate modelscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026Benchmarking Tabular Foundation Models for Conditional Density Estimation in Regressioncited by 3
  2. 2026LoBoost: Fast Model-Native Local Conformal Prediction for Gradient-Boosted Treescited by 0
  3. 2026LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictionscited by 0
  4. 2026CREDO: Epistemic-Aware Conformalized Credal Envelopes for Regressioncited by 0
  5. 2026Conservative neural posterior estimation via distributionally robust trainingcited by 0
  6. 2026A Three-Way Testing Framework for Quantifying Epistemic Calibration Uncertainty in SBIcited by 0

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  5. 2026Empirical Bayes Conformal Prediction for Vision and Language Models
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