mlsanityData to 7 Oct 2026

Variational methods for simulation-based inference

arXiv 2203.04176 ↗First posted 8 Mar 2022stat.ML cs.LGcited by 43

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Abstract (arXiv)

We present Sequential Neural Variational Inference (SNVI), an approach to perform Bayesian inference in models with intractable likelihoods. SNVI combines likelihood-estimation (or likelihood-ratio-estimation) with variational inference to achieve a scalable simulation-based inference approach. SNVI maintains the flexibility of likelihood(-ratio) estimation to allow arbitrary proposals for simulations, while simultaneously providing a functional estimate of the posterior distribution without requiring MCMC sampling. We present several variants of SNVI and demonstrate that they are substantially more computationally efficient than previous algorithms, without loss of accuracy on benchmark tasks. We apply SNVI to a neuroscience model of the pyloric network in the crab and demonstrate that it can infer the posterior distribution with one order of magnitude fewer simulations than previously reported. SNVI vastly reduces the computational cost of simulation-based inference while maintaining accuracy and flexibility, making it possible to tackle problems that were previously inaccessible.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 35 of its 64 references that are in the map. First posted on arXiv 8 Mar 2022.

Builds on

35 of 64 references.

References · 35

  1. 2015Variational Inference with Normalizing Flowscited by 2,161
  2. 2016Density estimation using Real NVPcited by 2,029
  3. 2016Variational Inference: A Review for Statisticianscited by 1,466
  4. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,315
  5. 2017Masked Autoregressive Flow for Density Estimationcited by 680
  6. 2016Improving Variational Inference with Inverse Autoregressive Flowcited by 636
  7. 2019Neural Spline Flowscited by 590
  8. 2015Importance Weighted Autoencoderscited by 454
  9. 2018Pyro: Deep Universal Probabilistic Programmingcited by 379
  10. 2013Black Box Variational Inferencecited by 317
  11. 2016Revisiting Classifier Two-Sample Testscited by 258
  12. 2018Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flowscited by 217
23 more
  1. 2019Automatic Posterior Transformation for Likelihood-Free Inferencecited by 216
  2. 2017Flexible statistical inference for mechanistic models of neural dynamicscited by 162
  3. 2021Benchmarking Simulation-Based Inferencecited by 160
  4. 2016Learning in Implicit Generative Modelscited by 124
  5. 2016R'enyi Divergence Variational Inferencecited by 104
  6. 2017Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inferencecited by 97
  7. 2020On Contrastive Learning for Likelihood-free Inferencecited by 96
  8. 2015Approximating Likelihood Ratios with Calibrated Discriminative Classifierscited by 87
  9. 2016Likelihood-free inference by ratio estimationcited by 80
  10. 2018Tighter Variational Bounds are Not Necessarily Bettercited by 76
  11. 2020Neural Approximate Sufficient Statistics for Implicit Modelscited by 72
  12. 2018Likelihood-free inference with emulator networkscited by 61
  13. 2018Importance Weighting and Variational Inferencecited by 55
  14. 2018Doubly Reparameterized Gradient Estimators for Monte Carlo Objectivescited by 41
  15. 2017Variational Inference using Implicit Distributionscited by 39
  16. 2020Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimizationcited by 37
  17. 2017Reinterpreting Importance-Weighted Autoencoderscited by 36
  18. 2021Sequential Neural Posterior and Likelihood Approximationcited by 30
  19. 2021Truncated Marginal Neural Ratio Estimationcited by 30
  20. 2021Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergencecited by 29
  21. 2020f-Divergence Variational Inferencecited by 28
  22. 2014Likelihood-free inference via classificationcited by 13
  23. 2016Variational Bayes with Synthetic Likelihoodcited by 6

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Citing papers per year: 2022: 9; 2023: 14; 2024: 11; 2025: 7; 2026: 2.

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  1. 2024All-in-one simulation-based inferencecited by 71
  2. 2022Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Modelscited by 50
  3. 2023Learning Robust Statistics for Simulation-based Inference under Model Misspecificationcited by 48
  4. 2022Compositional Score Modeling for Simulation-based Inferencecited by 46
  5. 2023JANA: Jointly Amortized Neural Approximation of Complex Bayesian Modelscited by 41
  6. 2022Truncated proposals for scalable and hassle-free simulation-based inferencecited by 40
  7. 2024Neural Methods for Amortized Inferencecited by 36
  8. 2025Simulation-Based Inference: A Practical Guidecited by 30
  9. 2022Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimationcited by 27
  10. 2024Addressing Misspecification in Simulation-based Inference through Data-driven Calibrationcited by 26
  11. 2024sbi reloaded: a toolkit for simulation-based inference workflowscited by 23
  12. 2023Sensitivity-Aware Amortized Bayesian Inferencecited by 20
31 more
  1. 2023Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimationcited by 17
  2. 2023Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inferencecited by 14
  3. 2023Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networkscited by 13
  4. 2025Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Modelscited by 13
  5. 2023Simulation-based Inference for Cardiovascular Modelscited by 11
  6. 2023Balancing Simulation-based Inference for Conservative Posteriorscited by 10
  7. 2025Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluationcited by 10
  8. 2023Misspecification-robust Sequential Neural Likelihood for Simulation-based Inferencecited by 8
  9. 2023Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimationcited by 8
  10. 2024Compositional simulation-based inference for time seriescited by 8
  11. 2022Contrastive Neural Ratio Estimation for Simulation-based Inferencecited by 7
  12. 2022Efficient identification of informative features in simulation-based inferencecited by 5
  13. 2022Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inferencecited by 5
  14. 2024A Kernel-Based Conditional Two-Sample Test Using Nearest Neighbors (with Applications to Calibration, Regression Curves, and Simulation-Based Inference)cited by 5
  15. 2024Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VIcited by 5
  16. 2023Simulation-based Inference with the Generalized Kullback-Leibler Divergencecited by 3
  17. 2023Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inferencecited by 3
  18. 2024Demonstrating the power and flexibility of variational assumptions for amortized neural posterior estimation in environmental applicationscited by 3
  19. 2024Amortized Bayesian Workflowcited by 3
  20. 2022Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisationcited by 2
  21. 2024Variational Autoencoders for Efficient Simulation-Based Inferencecited by 2
  22. 2025Fast and Scalable Score-Based Kernel Calibration Testscited by 2
  23. 2023Goal-oriented Uncertainty Quantification for Inverse Problems via Variational Encoder-Decoder Networkscited by 1
  24. 2024SoftCVI: Contrastive variational inference with self-generated soft labelscited by 1
  25. 2025A New Stochastic Approximation Method for Gradient-based Simulated Parameter Estimationcited by 1
  26. 2025Causal Posterior Estimationcited by 1
  27. 2026Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimationcited by 1
  28. 2022An Optimal Likelihood Free Method for Biological Model Selectioncited by 0
  29. 2023An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimationcited by 0
  30. 2025Misspecification-robust amortised simulation-based inference using variational methodscited by 0
  31. 2026FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimationcited by 0