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Validating Bayesian Inference Algorithms with Simulation-Based Calibration

arXiv 1804.06788 ↗First posted 18 Apr 2018stat.MEcited by 124

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Abstract (arXiv)

Verifying the correctness of Bayesian computation is challenging. This is especially true for complex models that are common in practice, as these require sophisticated model implementations and algorithms. In this paper we introduce simulation-based calibration (SBC), a general procedure for validating inferences from Bayesian algorithms capable of generating posterior samples. This procedure not only identifies inaccurate computation and inconsistencies in model implementations but also provides graphical summaries that can indicate the nature of the problems that arise. We argue that SBC is a critical part of a robust Bayesian workflow, as well as being a useful tool for those developing computational algorithms and statistical software.

Key facts. Cited by 124 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Apr 2018.

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Citing papers per year: 2021: 8; 2022: 16; 2023: 21; 2024: 15; 2025: 22; 2026: 42.

124 papers.

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  1. 2021Benchmarking Simulation-Based Inferencecited by 162
  2. 2021Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networkscited by 49
  3. 2022Robust Neural Posterior Estimation and Statistical Model Criticismcited by 46
  4. 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inferencecited by 46
  5. 2022Truncated proposals for scalable and hassle-free simulation-based inferencecited by 41
  6. 2023JANA: Jointly Amortized Neural Approximation of Complex Bayesian Modelscited by 41
  7. 2024Neural Methods for Amortized Inferencecited by 39
  8. 2022GATSBI: Generative Adversarial Training for Simulation-Based Inferencecited by 36
  9. 2023BayesFlow: Amortized Bayesian Workflows With Neural Networkscited by 32
  10. 2025Simulation-Based Inference: A Practical Guidecited by 32
  11. 2021Sequential Neural Posterior and Likelihood Approximationcited by 30
  12. 2021A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithfulcited by 28
38 more
  1. 2022Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimationcited by 28
  2. 2024Amortized Probabilistic Conditioning for Optimization, Simulation and Inferencecited by 23
  3. 2024sbi reloaded: a toolkit for simulation-based inference workflowscited by 23
  4. 2023Consistency Models for Scalable and Fast Simulation-Based Inferencecited by 22
  5. 2023Sensitivity-Aware Amortized Bayesian Inferencecited by 20
  6. 2023L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inferencecited by 18
  7. 2022Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimizationcited by 15
  8. 2023Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inferencecited by 14
  9. 2024Amortized Bayesian Multilevel Modelscited by 14
  10. 2022Black-box Bayesian inference for economic agent-based modelscited by 13
  11. 2023A Deep Learning Method for Comparing Bayesian Hierarchical Modelscited by 12
  12. 2021Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inferencecited by 11
  13. 2023Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probabilitycited by 11
  14. 2025Diffusion Models in Simulation-Based Inference: A Tutorial Reviewcited by 11
  15. 2022Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)cited by 10
  16. 2023Balancing Simulation-based Inference for Conservative Posteriorscited by 10
  17. 2024Compositional simulation-based inference for time seriescited by 9
  18. 2025Multifidelity Simulation-based Inference for Computationally Expensive Simulatorscited by 9
  19. 2026BayesFlow 2: Multi-Backend Amortized Bayesian Inference in Pythoncited by 9
  20. 2021Toward a Taxonomy of Trust for Probabilistic Machine Learningcited by 8
  21. 2022Validation Diagnostics for SBI algorithms based on Normalizing Flowscited by 8
  22. 2022Are you using test log-likelihood correctly?cited by 8
  23. 2023Misspecification-robust Sequential Neural Likelihood for Simulation-based Inferencecited by 8
  24. 2023Simultaneous identification of models and parameters of scientific simulatorscited by 8
  25. 2023Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimationcited by 8
  26. 2024Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigationcited by 8
  27. 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibrationcited by 8
  28. 2022Calibrating Agent-based Models to Microdata with Graph Neural Networkscited by 7
  29. 2022Contrastive Neural Ratio Estimation for Simulation-based Inferencecited by 7
  30. 2024A Kernel-Based Conditional Two-Sample Test Using Nearest Neighbors (with Applications to Calibration, Regression Curves, and Simulation-Based Inference)cited by 7
  31. 2024Conditional diffusions for amortized neural posterior estimationcited by 7
  32. 2026this-that-model-1.0: A typed decision model that decides in 30 ms, for a millionth of a centcited by 7
  33. 2024Calibrated Computation-Aware Gaussian Processescited by 6
  34. 2026Learning Probabilistic Filters with Strictly Proper Scoring Rulescited by 6
  35. 2022Efficient identification of informative features in simulation-based inferencecited by 5
  36. 2022Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Modelscited by 5
  37. 2024Listening to the Noise: Blind Denoising with Gibbs Diffusioncited by 5
  38. 2023Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inferencecited by 4

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