mlsanityData to 7 Oct 2026

Simulation-based Inference with the Generalized Kullback-Leibler Divergence

arXiv 2310.01808 ↗First posted 3 Oct 2023stat.ML cs.LG stat.COcited by 3

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Abstract (arXiv)

In Simulation-based Inference, the goal is to solve the inverse problem when the likelihood is only known implicitly. Neural Posterior Estimation commonly fits a normalized density estimator as a surrogate model for the posterior. This formulation cannot easily fit unnormalized surrogates because it optimizes the Kullback-Leibler divergence. We propose to optimize a generalized Kullback-Leibler divergence that accounts for the normalization constant in unnormalized distributions. The objective recovers Neural Posterior Estimation when the model class is normalized and unifies it with Neural Ratio Estimation, combining both into a single objective. We investigate a hybrid model that offers the best of both worlds by learning a normalized base distribution and a learned ratio. We also present benchmark results.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 34 of its 70 references that are in the map. First posted on arXiv 3 Oct 2023.

Builds on

34 of 70 references.

References · 34

  1. 2016Improved Techniques for Training GANscited by 2,938
  2. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,315
  3. 2017Masked Autoregressive Flow for Density Estimationcited by 680
  4. 2019Neural Spline Flowscited by 590
  5. 2019On Variational Bounds of Mutual Informationcited by 550
  6. 2016f-GAN: Training Generative Neural Samplers using Variational Divergence Minimizationcited by 504
  7. 2019The frontier of simulation-based inferencecited by 490
  8. 2021How to Train Your Energy-Based Modelscited by 271
  9. 2016Revisiting Classifier Two-Sample Testscited by 258
  10. 2018Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flowscited by 217
  11. 2019Automatic Posterior Transformation for Likelihood-Free Inferencecited by 216
  12. 2018Neural Autoregressive Flowscited by 207
22 more
  1. 2017Flexible statistical inference for mechanistic models of neural dynamicscited by 162
  2. 2021Benchmarking Simulation-Based Inferencecited by 160
  3. 2018Validating Bayesian Inference Algorithms with Simulation-Based Calibrationcited by 118
  4. 2020Telescoping Density-Ratio Estimationcited by 108
  5. 2016Likelihood-free inference by ratio estimationcited by 80
  6. 2021Real-time gravitational-wave science with neural posterior estimationcited by 76
  7. 2020Generalized Energy Based Modelscited by 73
  8. 2022Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Modelscited by 50
  9. 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inferencecited by 45
  10. 2022Variational methods for simulation-based inferencecited by 43
  11. 2022GATSBI: Generative Adversarial Training for Simulation-Based Inferencecited by 36
  12. 2020The Expressive Power of a Class of Normalizing Flow Modelscited by 35
  13. 2021Truncated Marginal Neural Ratio Estimationcited by 30
  14. 2021Diagnostics for Conditional Density Models and Bayesian Inference Algorithmscited by 26
  15. 2020Score Matched Neural Exponential Families for Likelihood-Free Inferencecited by 21
  16. 2021Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimationcited by 13
  17. 2022E-Valuating Classifier Two-Sample Testscited by 10
  18. 2023Balancing Simulation-based Inference for Conservative Posteriorscited by 10
  19. 2022Validation Diagnostics for SBI algorithms based on Normalizing Flowscited by 8
  20. 2022Testing the boundaries: Normalizing Flows for higher dimensional data setscited by 7
  21. 2022Contrastive Neural Ratio Estimation for Simulation-based Inferencecited by 7
  22. 2023On the Effectiveness of Hybrid Mutual Information Estimationcited by 6

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Citing papers per year: 2024: 1; 2025: 2.

3 papers.

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  3. 2025Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Designcited by 2