mlsanityData to 7 Oct 2026

The frontier of simulation-based inference

arXiv 1911.01429 ↗First posted 4 Nov 2019stat.ML cs.LG stat.MEcited by 490

Not on the map. Why?

Cited by 20 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Many domains of science have developed complex simulations to describe phenomena of interest. While these simulations provide high-fidelity models, they are poorly suited for inference and lead to challenging inverse problems. We review the rapidly developing field of simulation-based inference and identify the forces giving new momentum to the field. Finally, we describe how the frontier is expanding so that a broad audience can appreciate the profound change these developments may have on science.

Key facts. Cited by 490 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Nov 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 47; 2022: 50; 2023: 86; 2024: 88; 2025: 101; 2026: 118.

490 papers.

Sort:

By area:

  1. 2021Transformers Can Do Bayesian Inferencecited by 338
  2. 2021Benchmarking Simulation-Based Inferencecited by 160
  3. 2024The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learningcited by 134
  4. 2022Language Model Cascadescited by 104
  5. 2021gradSim: Differentiable simulation for system identification and visuomotor controlcited by 100
  6. 2023Flow Matching for Scalable Simulation-Based Inferencecited by 97
  7. 2021A Living Review of Machine Learning for Particle Physicscited by 77
  8. 2021Real-time gravitational-wave science with neural posterior estimationcited by 76
  9. 2024All-in-one simulation-based inferencecited by 71
  10. 2022On scientific understanding with artificial intelligencecited by 68
  11. 2021Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoodscited by 61
  12. 2021Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modelingcited by 59
38 more
  1. 2021Robot Learning from Randomized Simulations: A Reviewcited by 56
  2. 2022Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Modelscited by 50
  3. 2021Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networkscited by 48
  4. 2023Learning Robust Statistics for Simulation-based Inference under Model Misspecificationcited by 48
  5. 2022Compositional Score Modeling for Simulation-based Inferencecited by 46
  6. 2021Particle Cloud Generation with Message Passing Generative Adversarial Networkscited by 45
  7. 2022Robust Neural Posterior Estimation and Statistical Model Criticismcited by 45
  8. 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inferencecited by 45
  9. 2022Investigating the Impact of Model Misspecification in Neural Simulation-based Inferencecited by 44
  10. 2022UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translationcited by 42
  11. 2022Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrapcited by 41
  12. 2023JANA: Jointly Amortized Neural Approximation of Complex Bayesian Modelscited by 41
  13. 2023Infinite-Dimensional Diffusion Modelscited by 38
  14. 2022Physical Design using Differentiable Learned Simulatorscited by 37
  15. 2023Conditional score-based diffusion models for Bayesian inference in infinite dimensionscited by 37
  16. 2022GATSBI: Generative Adversarial Training for Simulation-Based Inferencecited by 36
  17. 2024Neural Methods for Amortized Inferencecited by 36
  18. 2024Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physicscited by 36
  19. 2021Sequential Neural Posterior and Likelihood Approximationcited by 30
  20. 2021Truncated Marginal Neural Ratio Estimationcited by 30
  21. 2025Simulation-Based Inference: A Practical Guidecited by 30
  22. 2021Neural Networks for Parameter Estimation in Intractable Modelscited by 28
  23. 2022Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inferencecited by 28
  24. 2021A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithfulcited by 27
  25. 2022Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimationcited by 27
  26. 2021Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Boundscited by 26
  27. 2024Addressing Misspecification in Simulation-based Inference through Data-driven Calibrationcited by 26
  28. 2025Walrus: A Cross-Domain Foundation Model for Continuum Dynamicscited by 26
  29. 2022Reliable amortized variational inference with physics-based latent distribution correctioncited by 25
  30. 2024Dynamic Conditional Optimal Transport through Simulation-Free Flowscited by 24
  31. 2023End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physicscited by 22
  32. 2023Distribution learning via neural differential equations: a nonparametric statistical perspectivecited by 22
  33. 2023Consistency Models for Scalable and Fast Simulation-Based Inferencecited by 22
  34. 2024Marrying Causal Representation Learning with Dynamical Systems for Sciencecited by 22
  35. 2024Amortized Probabilistic Conditioning for Optimization, Simulation and Inferencecited by 22
  36. 2025The Reality Gap in Robotics: Challenges, Solutions, and Best Practicescited by 22
  37. 2022Scientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomenacited by 21
  38. 2024Real-time gravitational-wave inference for binary neutron stars using machine learningcited by 21

50 most cited of 490 All 490 (JSON)