mlsanityData to 7 Oct 2026

Compositional Score Modeling for Simulation-based Inference

arXiv 2209.14249 ↗First posted 28 Sep 2022cs.LG stat.MLcited by 46

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Abstract (arXiv)

Neural Posterior Estimation methods for simulation-based inference can be ill-suited for dealing with posterior distributions obtained by conditioning on multiple observations, as they tend to require a large number of simulator calls to learn accurate approximations. In contrast, Neural Likelihood Estimation methods can handle multiple observations at inference time after learning from individual observations, but they rely on standard inference methods, such as MCMC or variational inference, which come with certain performance drawbacks. We introduce a new method based on conditional score modeling that enjoys the benefits of both approaches. We model the scores of the (diffused) posterior distributions induced by individual observations, and introduce a way of combining the learned scores to approximately sample from the target posterior distribution. Our approach is sample-efficient, can naturally aggregate multiple observations at inference time, and avoids the drawbacks of standard inference methods.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). Builds on 41 of its 70 references that are in the map. First posted on arXiv 28 Sep 2022.

Builds on

41 of 70 references.

References · 41

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 4; 2024: 10; 2025: 18; 2026: 13.

46 papers.

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  1. 2024All-in-one simulation-based inferencecited by 71
  2. 2024Amortizing intractable inference in diffusion models for vision, language, and controlcited by 70
  3. 2022Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Modelscited by 50
  4. 2025Simulation-Based Inference: A Practical Guidecited by 30
  5. 2024Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Predictioncited by 28
  6. 2024Diffusion posterior sampling for simulation-based inference in tall data settingscited by 17
  7. 2023Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inferencecited by 14
  8. 2025Amortized In-Context Bayesian Posterior Estimationcited by 13
  9. 2025Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Modelscited by 13
  10. 2024Does learning the right latent variables necessarily improve in-context learning?cited by 12
  11. 2024Amortized Bayesian Multilevel Modelscited by 12
  12. 2023Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimationcited by 8
34 more
  1. 2024Compositional simulation-based inference for time seriescited by 8
  2. 2024Conditional diffusions for amortized neural posterior estimationcited by 6
  3. 2025Product of Experts for Visual Generationcited by 6
  4. 2025Robust Simulation-Based Inference under Missing Data via Neural Processescited by 5
  5. 2025Multilevel neural simulation-based inferencecited by 5
  6. 2025CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inferencecited by 5
  7. 2026Zero-Flow Encoderscited by 4
  8. 2023Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inferencecited by 3
  9. 2024Amortized Bayesian Workflowcited by 3
  10. 2025Posterior SBC: Simulation-Based Calibration Checking Conditional on Datacited by 3
  11. 2025FNOPE: Simulation-based inference on function spaces with Fourier Neural Operatorscited by 3
  12. 2025PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inferencecited by 3
  13. 2023Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layerscited by 2
  14. 2025Synthesizing 3D Abstractions by Inverting Procedural Buildings with Transformerscited by 1
  15. 2025Diffusion Models for Inverse Problems in the Exponential Familycited by 1
  16. 2025Causal Posterior Estimationcited by 1
  17. 2025Conformal C2ST: Turning weak classifiers into strong two-sample testscited by 1
  18. 2025Error analysis of a compositional score-based algorithm for simulation-based inferencecited by 1
  19. 2025A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarioscited by 1
  20. 2026Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimationcited by 1
  21. 2026Latent Target Score Matching, with an application to Simulation-Based Inferencecited by 1
  22. 2026It Just Takes Two: Scaling Amortized Inference to Large Setscited by 1
  23. 2026An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learningcited by 1
  24. 2024Diffusion Generative Modelling for Divide-and-Conquer MCMCcited by 0
  25. 2025Direct Fisher Score Estimation for Likelihood Maximizationcited by 0
  26. 2025CoLT: The conditional localization test for assessing the accuracy of neural posterior estimatescited by 0
  27. 2026OneFlowSBI: One Model, Many Queries for Simulation-Based Inferencecited by 0
  28. 2026Tokenised Flow Matching for Hierarchical Simulation Based Inferencecited by 0
  29. 2026Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inferencecited by 0
  30. 2026Amortized Factor Inference Networks for Posterior Inferencecited by 0
  31. 2026MA-SBI: Misspecification-Aware Simulation-Based Inference via Side-Channel Guidancecited by 0
  32. 2026FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimationcited by 0
  33. 2026Neural composite likelihood estimation: simulation based inference for time seriescited by 0
  34. 2026A Three-Way Testing Framework for Quantifying Epistemic Calibration Uncertainty in SBIcited by 0