mlsanityData to 7 Oct 2026

Investigating the Impact of Model Misspecification in Neural Simulation-based Inference

arXiv 2209.01845 ↗First posted 5 Sep 2022stat.ML cs.LG stat.COcited by 44

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Abstract (arXiv)

Aided by advances in neural density estimation, considerable progress has been made in recent years towards a suite of simulation-based inference (SBI) methods capable of performing flexible, black-box, approximate Bayesian inference for stochastic simulation models. While it has been demonstrated that neural SBI methods can provide accurate posterior approximations, the simulation studies establishing these results have considered only well-specified problems -- that is, where the model and the data generating process coincide exactly. However, the behaviour of such algorithms in the case of model misspecification has received little attention. In this work, we provide the first comprehensive study of the behaviour of neural SBI algorithms in the presence of various forms of model misspecification. We find that misspecification can have a profoundly deleterious effect on performance. Some mitigation strategies are explored, but no approach tested prevents failure in all cases. We conclude that new approaches are required to address model misspecification if neural SBI algorithms are to be relied upon to derive accurate scientific conclusions.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). Builds on 30 of its 55 references that are in the map. First posted on arXiv 5 Sep 2022.

Builds on

30 of 55 references.

References · 30

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,888
  3. 2020Sharpness-Aware Minimization for Efficiently Improving Generalizationcited by 1,404
  4. 2016On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minimacited by 1,337
  5. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,315
  6. 2018Averaging Weights Leads to Wider Optima and Better Generalizationcited by 1,194
  7. 2019Neural Spline Flowscited by 590
  8. 2019A Simple Baseline for Bayesian Uncertainty in Deep Learningcited by 555
  9. 2019The frontier of simulation-based inferencecited by 490
  10. 2020Bayesian Deep Learning and a Probabilistic Perspective of Generalizationcited by 480
  11. 2018Do Deep Generative Models Know What They Don't Know?cited by 443
  12. 2018Pyro: Deep Universal Probabilistic Programmingcited by 379
18 more
  1. 2018Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flowscited by 217
  2. 2019Automatic Posterior Transformation for Likelihood-Free Inferencecited by 216
  3. 2013A General Framework for Updating Belief Distributionscited by 172
  4. 2021Benchmarking Simulation-Based Inferencecited by 160
  5. 2019A Primer on PAC-Bayesian Learningcited by 130
  6. 2020On Contrastive Learning for Likelihood-free Inferencecited by 96
  7. 2016Likelihood-free inference by ratio estimationcited by 80
  8. 2019Generalized Variational Inference: Three arguments for deriving new Posteriorscited by 57
  9. 2022Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrapcited by 41
  10. 2020Complete parameter inference for GW150914 using deep learningcited by 25
  11. 2020Generalized Posteriors in Approximate Bayesian Computationcited by 19
  12. 2019Robust Approximate Bayesian Inference with Synthetic Likelihoodcited by 14
  13. 2022Black-box Bayesian inference for economic agent-based modelscited by 13
  14. 2021Approximate Bayesian Computation with Path Signaturescited by 12
  15. 2022Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimationcited by 8
  16. 2020Robust Approximate Bayesian Computation: An Adjustment Approachcited by 5
  17. 2021Synthetic likelihood in misspecified modelscited by 5
  18. 2017Probably approximate Bayesian computation: nonasymptotic convergence of ABC under misspecificationcited by 2

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Citing papers per year: 2022: 3; 2023: 11; 2024: 11; 2025: 10; 2026: 9.

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  1. 2023Learning Robust Statistics for Simulation-based Inference under Model Misspecificationcited by 48
  2. 2022Robust Neural Posterior Estimation and Statistical Model Criticismcited by 45
  3. 2025Simulation-Based Inference: A Practical Guidecited by 30
  4. 2022Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inferencecited by 28
  5. 2024Addressing Misspecification in Simulation-based Inference through Data-driven Calibrationcited by 26
  6. 2023Sensitivity-Aware Amortized Bayesian Inferencecited by 20
  7. 2023Adversarial robustness of amortized Bayesian inferencecited by 17
  8. 2023Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimationcited by 17
  9. 2024The Statistical Accuracy of Neural Posterior and Likelihood Estimationcited by 15
  10. 2025Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluationcited by 10
  11. 2025Multifidelity Simulation-based Inference for Computationally Expensive Simulatorscited by 9
  12. 2025Simulation-based Bayesian inference under model misspecificationcited by 9
32 more
  1. 2023Misspecification-robust Sequential Neural Likelihood for Simulation-based Inferencecited by 8
  2. 2024Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigationcited by 8
  3. 2024Compositional simulation-based inference for time seriescited by 8
  4. 2024Domain-Adaptive Neural Posterior Estimation for Strong Gravitational Lens Analysiscited by 7
  5. 2024Preconditioned Neural Posterior Estimation for Likelihood-free Inferencecited by 6
  6. 2023AI for Science: An Emerging Agendacited by 5
  7. 2024A Comprehensive Guide to Simulation-based Inference in Computational Biologycited by 5
  8. 2023Bayesian calibration of differentiable agent-based modelscited by 4
  9. 2023Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networkscited by 4
  10. 2024Tests for model misspecification in simulation-based inference: from local distortions to global model checkscited by 4
  11. 2025Inductive Domain Transfer In Misspecified Simulation-Based Inferencecited by 4
  12. 2024Predictive variational inference: Learn the predictively optimal posterior distributioncited by 3
  13. 2026Minimum Distance Summaries for Robust Neural Posterior Estimationcited by 3
  14. 2023Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layerscited by 2
  15. 2023Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inferencecited by 1
  16. 2023Amortized Bayesian Decision Making for simulation-based modelscited by 1
  17. 2024R'enyi Neural Processescited by 1
  18. 2024SoftCVI: Contrastive variational inference with self-generated soft labelscited by 1
  19. 2025Synthesizing 3D Abstractions by Inverting Procedural Buildings with Transformerscited by 1
  20. 2025Flow Matching Calibration for Simulation-Based Inference under Model Misspecificationcited by 1
  21. 2025Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inferencecited by 1
  22. 2026Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimationcited by 1
  23. 2026Scalable Simulation-Based Model Inference with Test-Time Complexity Controlcited by 1
  24. 2026An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learningcited by 1
  25. 2026Unknown Unknowns: Model Misspecification in Machine Learning for Physicscited by 1
  26. 2022Calibrating AI Models for Wireless Communications via Conformal Predictioncited by 0
  27. 2025Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecificationcited by 0
  28. 2025Misspecification-robust amortised simulation-based inference using variational methodscited by 0
  29. 2026Preconditioned Robust Neural Posterior Estimation for Misspecified Simulatorscited by 0
  30. 2026Unsupervised Continual Learning for Amortized Bayesian Inferencecited by 0
  31. 2026Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inferencecited by 0
  32. 2026Mixed neural posterior estimation for simulators with discrete and continuous parameterscited by 0