mlsanityData to 14 Oct 2026

Simulation-based Bayesian inference under model misspecification

arXiv 2503.12315 ↗First posted 16 Mar 2025stat.ME cs.LG stat.COcited by 9

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Abstract (arXiv)

Simulation-based Bayesian inference (SBI) methods are widely used for parameter estimation in complex models where evaluating the likelihood is challenging but generating simulations is relatively straightforward. However, these methods commonly assume that the simulation model accurately reflects the true data-generating process, an assumption that is frequently violated in realistic scenarios. In this paper, we focus on the challenges faced by SBI methods under model misspecification. We consolidate recent research aimed at mitigating the effects of misspecification, highlighting three key strategies: i) robust summary statistics, ii) generalised Bayesian inference, and iii) error modelling and adjustment parameters. To illustrate both the vulnerabilities of popular SBI methods and the effectiveness of misspecification-robust alternatives, we present empirical results on an illustrative example.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 79 of its 157 references that are in the map. First posted on arXiv 16 Mar 2025.

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79 of 157 references.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 4.

9 papers.

  1. 2025Diffusion Models in Simulation-Based Inference: A Tutorial Reviewcited by 11
  2. 2025G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibrationcited by 8
  3. 2026Minimum Distance Summaries for Robust Neural Posterior Estimationcited by 3
  4. 2025Representative, Informative, and De-Amplifying: Requirements for Robust Bayesian Active Learning under Model Misspecificationcited by 2
  5. 2025Flow Matching Calibration for Simulation-Based Inference under Model Misspecificationcited by 2
  6. 2026Scalable Simulation-Based Model Inference with Test-Time Complexity Controlcited by 2
  7. 2025Misspecification-robust amortised simulation-based inference using variational methodscited by 0
  8. 2026Preconditioned Robust Neural Posterior Estimation for Misspecified Simulatorscited by 0
  9. 2026Mixed neural posterior estimation for simulators with discrete and continuous parameterscited by 0