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awesome-neural-sbi

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Community-sourced list of papers and resources on neural simulation-based inference.

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<h1 align="center">
Awesome Neural SBI
</h1>

[![License: MIT](https://img.shields.io/badge/License-MIT-red.svg)](https://opensource.org/licenses/MIT)
[![Pull requests welcome](https://img.shields.io/badge/Pull%20Requests-welcome-green.svg?logo=github)](https://github.com/smsharma/awesome-neural-sbi/pulls)
</h4>

A community-sourced list of papers and resources on neural simulation-based inference, covering both methodological developments and domain applications. Given the nature of the field, the list is bound to be highly incomplete -- contributions are welcome!

# Contents

- [Software and Resources](#software-and-resources)
  - [Code Packages and Benchmarks](#code-packages-and-benchmarks)
  - [Tutorials](#tutorials)
  - [Review Papers](#review-papers)
  - [Discovery and Links](#discovery-and-links)
- [Papers: Methods](#papers-methods)
- [Papers: Application](#papers-application)
  - [Cosmology, Astrophysics, and Astronomy](#cosmology-astrophysics-and-astronomy)
  - [Particle Physics](#particle-physics)
  - [Neuroscience and Cognitive Science](#neuroscience-and-cognitive-science)
  - [Health and Medicine](#health-and-medicine)
  - [Other Domains](#other-domains)
  - [Application to Real Data](#application-to-real-data)

# Software and Resources
  
## Code Packages and Benchmarks

- `sbi` [[Code]](https://github.com/mackelab/sbi) [[Docs]](https://www.mackelab.org/sbi/) [[Paper]](https://joss.theoj.org/papers/10.21105/joss.02505): General-purpose simulation-based inference toolkit.
- `BayesFlow` [[Code]](https://github.com/stefanradev93/BayesFlow) [[Docs]](https://bayesflow.org/) [[Paper]](https://joss.theoj.org/papers/10.21105/joss.05702): Simulation-based inference framework with a focus on amortized Bayesian workflows.
- `sbibm` [[Code]](https://github.com/sbi-benchmark/sbibm) [[Docs]](https://sbi-benchmark.github.io/) [[Paper]](https://arxiv.org/abs/2312.03824): Simulation-based inference benchmarking framework.
- `swyft` [[Code]](https://github.com/undark-lab/swyft) [[Docs]](https://swyft.readthedocs.io/en/latest/) [[Paper]](https://joss.theoj.org/papers/10.21105/joss.04205): Official implementation of Truncated Marginal Neural Ratio Estimation (TMNRE), a hyper-efficient, simulation-based inference technique for complex data and expensive simulators.
- `NeuralEstimators.jl` [[Code]](https://github.com/msainsburydale/NeuralEstimators.jl) [[Docs]](https://msainsburydale.github.io/NeuralEstimators.jl/dev/): Amortized neural inference in Julia.
- `SimulationBasedInference.jl` [[Code]](https://github.com/bgroenks96/SimulationBasedInference.jl) [[Docs]](https://bgroenks96.github.io/SimulationBasedInference.jl/dev/): Simulation-based inference in Julia.
- `sbiax` [[Code]](https://github.com/homerjed/sbiax) [[Paper]](https://arxiv.org/abs/2412.02311): Density-estimation Simulation-based inference in JAX.
- `lampe` [[Code]](https://github.com/francois-rozet/lampe) [[Docs]](https://lampe.readthedocs.io): Likelihood-free AMortized Posterior Estimation with PyTorch.
- `sbijax` [[Code]](https://github.com/dirmeier/sbijax) [[Paper]](https://arxiv.org/abs/2409.19435): Simulation-based inference in JAX.
- `nbi` [[Code]](https://github.com/kmzzhang/nbi) [[Docs]](https://nbi.readthedocs.io/en/latest/) [[Paper]](https://arxiv.org/abs/2312.03824): Neural Posterior Estimation (NPE) package with a focus on astronomical light curves and spectra.
- `MadMiner` [[Code]](https://github.com/madminer-tool/madminer) [[Docs]](https://madminer.readthedocs.io/en/latest/index.html) [[Paper]](https://arxiv.org/abs/1907.10621): Machine learning–based inference toolkit for particle physics.
- `pydelfi` [[Code]](https://github.com/justinalsing/pydelfi) [[Docs]](https://pydelfi.readthedocs.io/en/latest/intro.html) [[Paper]](https://arxiv.org/abs/1903.00007): Early implementation of Density Estimation Likelihood-Free Inference (DELFI) with neural density estimators and adaptive acquisition of simulations.
- `carl` [[Code]](https://github.com/diana-hep/carl) [[Docs]](http://diana-hep.org/carl/) [[Paper]](https://joss.theoj.org/papers/10.21105/joss.00011): Early toolbox for neural network-based likelihood-free inference in Python.

## Tutorials

- [SBI Tutorial](https://github.com/smsharma/sbi-lecture-mit): A hands-on tutorial introducing basic SBI concepts and methods.

## Review Papers

- **Simulation-Based Inference: A Practical Guide** [[arXiv]](https://arxiv.org/abs/2508.12939)
  Michael Deistler, Jan Boelts, Peter Steinbach, Guy Moss, Thomas Moreau, Manuel Gloeckler, Pedro L. C. Rodrigues, Julia Linhart, Janne K. Lappalainen, Benjamin Kurt Miller, Pedro J. Gonçalves, Jan-Matthis Lueckmann, Cornelius Schröder, Jakob H. Macke

- **Diffusion Models in Simulation-Based Inference: A Tutorial Review** [[arXiv]](https://arxiv.org/abs/2512.20685) [[Paper]](https://bayesflow-org.github.io/diffusion-experiments/)
  Jonas Arruda, Niels Bracher, Ullrich Köthe, Jan Hasenauer, Stefan T. Radev

- **A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios** [[arXiv]](https://arxiv.org/abs/2512.23748)
  Haley Rosso, Talea Mayo

- **Simulation-based Bayesian inference under model misspecification** [[arXiv]](https://arxiv.org/abs/2503.12315)
  Ryan P. Kelly, David J. Warne, David T. Frazier, David J. Nott, Michael U. Gutmann, Christopher Drovandi

- **Neural Methods for Amortized Inference** [[arXiv]](https://arxiv.org/abs/2404.12484)
  Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser

- **The frontier of simulation-based inference** [[arXiv]](https://arxiv.org/abs/1911.01429)
  Kyle Cranmer, Johann Brehmer, Gilles Louppe

## Discovery and Links

- [arXiv search](https://arxiv.org/search/advanced?advanced=1&terms-0-operator=AND&terms-0-term=%22simulation-based+inference%22+&terms-0-field=all&terms-1-operator=OR&terms-1-term=%22likelihood-free+inference%22&terms-1-field=all&classification-computer_science=y&classification-mathematics=y&classification-physics=y&classification-physics_archives=all&classification-q_biology=y&classification-statistics=y&classification-include_cross_list=include&date-filter_by=all_dates&date-year=&date-from_date=&date-to_date=&date-date_type=submitted_date&abstracts=show&size=50&order=-announced_date_first) for "simulation-based inference" or "likelihood-free inference"
- [Google Scholar search](https://scholar.google.com/scholar?hl=en&scisbd=1&as_sdt=0%2C22&q=%22simulation-based+inference%22+OR+%22likelihood-free+inference%22&btnG=) for "simulation-based inference" or "likelihood-free inference"
- [simulation-based-inference.org](http://simulation-based-inference.org/): Community resource on simulation-based inference, including an automatically-compiled [list of papers](http://simulation-based-inference.org/papers/).

# Papers: Methods
*Methodological and use-inspired papers. Listed in reverse-chronological order.*

- **Misspecification-robust amortised simulation-based inference using variational methods** [[arXiv]](https://arxiv.org/abs/2509.05724)
  Matthew O'Callaghan, Kaisey S. Mandel, Gerry Gilmore

- **CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2508.17077)
  Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos, Pedro L. C. Rodrigues, Rafael Izbicki

- **Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation** [[arXiv]](https://arxiv.org/abs/2507.08734)
  Paul Bastide, Arnaud Estoup, Jean-Michel Marin, Julien Stoehr

- **Compositional amortized inference for large-scale hierarchical Bayesian models** [[arXiv]](https://arxiv.org/abs/2505.14429)
  Jonas Arruda, Vikas Pandey, Catherine Sherry, Margarida Barroso, Xavier Intes, Jan Hasenauer, Stefan T. Radev

- **Cosmological Parameter Estimation with Sequential Linear Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2501.03921)
  Nicolas Mediato-Diaz, Will Handley

- **Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data** [[arXiv]](https://arxiv.org/abs/2501.13483)
  Aayush Mishra, Daniel Habermann, Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner

- **Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2412.05590)
  Sam Griesemer, Defu Cao, Zijun Cui, Carolina Osorio, Yan Liu

- **sbi reloaded: a toolkit for simulation-based inference workflows** [[arXiv]](https://arxiv.org/abs/2411.17337)
  Jan Boelts, Michael Deistler, Manuel Gloeckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann et al.

- **PolySwyft: sequential simulation-based nested sampling** [[arXiv]](https://arxiv.org/abs/2512.08316)
  Kilian H. Scheutwinkel, Will Handley, Christoph Weniger, Eloy de Lera Acedo

- **Assessment of Simulation-based Inference Methods for Stochastic Compartmental Models** [[arXiv]](https://arxiv.org/abs/2512.02528)
  Vincent Wieland, Nils Wassmuth, Lorenzo Contento, Martin Kühn, Jan Hasenauer

- **Fast and Robust Simulation-Based Inference With Optimization Monte Carlo** [[arXiv]](https://arxiv.org/abs/2511.13394)
  Vasilis Gkolemis, Christos Diou, Michael Gutmann

- **ASBI: Leveraging Informative Real-World Data for Active Black-Box Simulator Tuning** [[arXiv]](https://arxiv.org/abs/2510.15331)
  Gahee Kim, Takamitsu Matsubara

- **Error analysis of a compositional score-based algorithm for simulation-based inference** [[arXiv]](https://arxiv.org/abs/2510.15817)
  Camille Touron, Gabriel V. Cardoso, Julyan Arbel, Pedro L. C. Rodrigues

- **Heuristic Adaptation of Potentially Misspecified Domain Support for Likelihood-Free Inference in Stochastic Dynamical Systems** [[arXiv]](https://arxiv.org/abs/2510.26656)
  Georgios Kamaras, Craig Innes, Subramanian Ramamoorthy

- **Tests for model misspecification in simulation-based inference: from local distortions to global model checks** [[arXiv]](https://arxiv.org/abs/2412.15100)
  Noemi Anau Montel, James Alvey, Christoph Weniger

- **Simulation-based Inference has its own Dodelson-Schneider Effect (but it knows that it does)** [[ArXiv]](https://arxiv.org/abs/2412.02311)
  Jed Homer, Oliver Friedrich, Daniel Gruen

- **Low-Budget Simulation-Based Inference with Bayesian Neural Networks** [[arXiv]](https://arxiv.org/abs/2408.15136)  
  Arnaud Delaunoy, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma, Gilles Louppe

- **Flow Matching for Posterior Inference with Simulator Feedback** [[arXiv]](https://arxiv.org/abs/2410.22573)  
  Benjamin Holzschuh, Nils Thuerey

- **Compositional simulation-based inference for time series** [[arXiv]](https://arxiv.org/abs/2411.02728)  
  Manuel Gloeckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke

- **Cost-aware Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2410.07930)  
  Ayush Bharti, Daolang Huang, Samuel Kaski, François-Xavier Briol

- **Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation** [[arXiv]](https://arxiv.org/abs/2406.03154)  
  Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

- **Addressing Misspecification in Simulation-based Inference through Data-driven Calibration** [[arXiv]](https://arxiv.org/abs/2405.08719)  
  Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Marco Cuturi, Jörn-Henrik Jacobsen

- **Preconditioned Neural Posterior Estimation for Likelihood-free Inference** [[arXiv]](https://arxiv.org/abs/2404.13557)  
  Xiaoyu Wang, Ryan P. Kelly, David J. Warne, Christopher Drovandi

- **All-in-one simulation-based inference** [[arXiv]](https://arxiv.org/abs/2404.09636)  
  Manuel Gloeckler, Michael Deistler, Christian Weilbach, Frank Wood, Jakob H. Macke

- **Diffusion posterior sampling for simulation-based inference in tall data settings** [[arXiv]](https://arxiv.org/abs/2404.07593)  
  Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues

- **Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings** [[arXiv]](https://arxiv.org/abs/2403.07454)  
  Henrik Häggström, Pedro L. C. Rodrigues, Geoffroy Oudoumanessah, Florence Forbes, Umberto Picchini

- **Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference** [[arXiv]](https://arxiv.org/abs/2402.05330)  
Luca Masserano, Alex Shen, Michele Doro, Tommaso Dorigo, Rafael Izbicki, Ann B. Lee

- **Simulation-Based Inference with Quantile Regression** [[arXiv]](https://arxiv.org/abs/2401.02413)  
He Jia

- **Consistency Models for Scalable and Fast Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2312.05440)  
Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T Radev

- **Pseudo-Likelihood Inference** [[arXiv]](https://arxiv.org/abs/2311.16656)  
Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters

- **Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2311.10671)  
Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner

- **Direct Amortized Likelihood Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2311.10571)  
Adam D. Cobb, Brian Matejek, Daniel Elenius, Anirban Roy, Susmit Jha

- **Simulation based stacking** [[arXiv]](https://arxiv.org/abs/2310.17009)  
Yuling Yao, Bruno Régaldo-Saint Blancard, Justin Domke

- **Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability** [[arXiv]](https://arxiv.org/abs/2310.13402)  
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis

- **Sensitivity-Aware Amortized Bayesian Inference** [[arXiv]](https://arxiv.org/abs/2310.11122)  
Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

- **Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference** [[arXiv]](https://arxiv.org/abs/2310.04395)  
Marvin Schmitt, Daniel Habermann, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

- **Simulation-based Inference with the Generalized Kullback-Leibler Divergence** [[arXiv]](https://arxiv.org/abs/2310.01808)  
Benjamin Kurt Miller, Marco Federici, Christoph Weniger, Patrick Forré

- **Data assimilation as simulation-based inference** [[Master thesis]](https://matheo.uliege.be/handle/2268.2/18255)  
Gérôme Andry, Gilles Louppe

- **A transport approach to sequential simulation-based inference** [[arXiv]](https://arxiv.org/abs/2308.13940)  
Paul-Baptiste Rubio, Youssef Marzouk, Matthew Parno

- **Kernel-Based Tests for Likelihood-Free Hypothesis Testing** [[arXiv]](https://arxiv.org/abs/2308.09043)  
Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy, Rui Sun

- **Scalable inference with Autoregressive Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2308.08597)  
Noemi Anau Montel, James Alvey, Christoph Weniger

- **Simulation-based inference using surjective sequential neural likelihood estimation** [[arXiv]](https://arxiv.org/abs/2308.01054)  
Simon Dirmeier, Carlo Albert, Fernando Perez-Cruz

- **Hierarchical Neural Simulation-Based Inference Over Event Ensembles** [[arXiv]](https://arxiv.org/abs/2306.12584)  
Lukas Heinrich, Siddharth Mishra-Sharma, Chris Pollard, Philipp Windischhofer

- **L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2306.03580)  
Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues

- **Flow Matching for Scalable Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2305.17161)  
Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf

- **Learning Robust Statistics for Simulation-based Inference under Model Misspecification** [[arXiv]](https://arxiv.org/abs/2305.15871)  
Daolang Huang, Ayush Bharti, Amauri Souza, Luigi Acerbi, Samuel Kaski

- **Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation** [[arXiv]](https://arxiv.org/abs/2305.15208)  
Richard Gao, Michael Deistler, Jakob H. Macke

- **Simultaneous identification of models and parameters of scientific simulators** [[arXiv]](https://arxiv.org/abs/2305.15174)  
Cornelius Schröder, Jakob H. Macke

- **Discriminative calibration** [[arXiv]](https://arxiv.org/abs/2305.14593)  
Yuling Yao, Justin Domke

- **Variational Inference with Coverage Guarantees** [[arXiv]](https://arxiv.org/abs/2305.14275)  
Yash Patel, Declan McNamara, Jackson Loper, Jeffrey Regier, Ambuj Tewari

- **Disentangled Multi-Fidelity Deep Bayesian Active Learning** [[arXiv]](https://arxiv.org/abs/2305.04392)  
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu

- **Balancing Simulation-based Inference for Conservative Posteriors** [[arXiv]](https://arxiv.org/abs/2304.10978)  
Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe

- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models** [[arXiv]](https://arxiv.org/abs/2302.09125)  
Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner

- **Sampling-Based Accuracy Testing of Posterior Estimators for General Inference** [[arXiv]](https://arxiv.org/abs/2302.03026)  
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault-Levasseur

- **Misspecification-robust Sequential Neural Likelihood** [[arXiv]](https://arxiv.org/abs/2301.13368)  
Ryan P. Kelly, David J. Nott, David T. Frazier, David J. Warne, Chris Drovandi

- **A Deep Learning Method for Comparing Bayesian Hierarchical Models** [[arXiv]](https://arxiv.org/abs/2301.11873)  
Lasse Elsemüller, Martin Schnuerch, Paul-Christian Bürkner, Stefan T. Radev

- **Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Models** [[arXiv]](https://arxiv.org/abs/2211.13165)  
Lukas Schumacher, Paul-Christian Bürkner, Andreas Voss, Ullrich Köthe, Stefan T. Radev

- **Validation Diagnostics for SBI algorithms based on Normalizing Flows** [[arXiv]](https://arxiv.org/abs/2211.09602)  
Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues

- **Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2211.03747)  
Bingjie Wang, Joel Leja, Ashley Villar, Joshua S. Speagle

- **Likelihood-free hypothesis testing** [[arXiv]](https://arxiv.org/abs/2211.01126)  
Patrik Róbert Gerber, Yury Polyanskiy

- **Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2210.14756)  
Pierre Glaser, Michael Arbel, Arnaud Doucet, Arthur Gretton

- **Efficient identification of informative features in simulation-based inference** [[arXiv]](https://arxiv.org/abs/2210.11915)  
Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob Macke, Philipp Berens

- **Robust Neural Posterior Estimation and Statistical Model Criticism** [[arXiv]](https://arxiv.org/abs/2210.06564)  
Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M Schmon

- **Contrastive Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2210.06170)  
Benjamin Kurt Miller, Christoph Weniger, Patrick Forré

- **Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models** [[arXiv]](https://arxiv.org/abs/2210.04872)  
Louis Sharrock, Jack Simons, Song Liu, Mark Beaumont

- **Truncated proposals for scalable and hassle-free simulation-based inference** [[arXiv]](https://arxiv.org/abs/2210.04815)  
Michael Deistler, Pedro J Goncalves, Jakob H Macke

- **New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2210.01680)  
Kyoungchul Kong, Konstantin T. Matchev, Stephen Mrenna, Prasanth Shyamsundar

- **Compositional Score Modeling for Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2209.14249)  
Tomas Geffner, George Papamakarios, Andriy Mnih

- **Investigating the Impact of Model Misspecification in Neural Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2209.01845)  
Patrick Cannon, Daniel Ward, Sebastian M. Schmon

- **Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2208.13624)  
Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe

- **Bayesian model comparison for simulation-based inference** [[arXiv]](https://arxiv.org/abs/2207.04037)
A. Spurio Mancini, M. M. Docherty, M. A. Price, J. D. McEwen

- **Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization** [[arXiv]](https://arxiv.org/abs/2205.15784)  
Lorenzo Pacchiardi, Ritabrata Dutta

- **Simulation-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems** [[arXiv]](https://arxiv.org/abs/2205.15680)  
Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

- **Learning Optimal Test Statistics in the Presence of Nuisance Parameters** [[arXiv]](https://arxiv.org/abs/2203.13079)  
Lukas Heinrich

- **GATSBI: Generative Adversarial Training for Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2203.06481)  
Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Álvaro Tejero-Cantero, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke

- **Variational methods for simulation-based inference** [[arXiv]](https://arxiv.org/abs/2203.04176)  
Manuel Glöckler, Michael Deistler, Jakob H. Macke

- **Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap** [[arXiv]](https://arxiv.org/abs/2202.04744)  
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol

- **Flexible and efficient simulation-based inference for models of decision-making** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2021.12.22.473472v3)  
Jan Boelts, Jan-Matthis Lueckmann, Richard Gao, Jakob H. Macke

- **Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks** [[arXiv]](https://arxiv.org/abs/2112.08866)  
Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev

- **Group equivariant neural posterior estimation** [[arXiv]](https://arxiv.org/abs/2111.13139)  
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke

- **A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful** [[arXiv]](https://arxiv.org/abs/2110.06581)  
Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe

- **Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2110.00449)  
François Rozet, Gilles Louppe

- **Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage** [[arXiv]](https://arxiv.org/abs/2107.03920)  
Niccolò Dalmasso, Luca Masserano, David Zhao, Rafael Izbicki, Ann B. Lee

- **Truncated Marginal Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2107.01214)  [[Code]](https://github.com/undark-lab/swyft/)  
Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger

- **MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled Trajectories** [[arXiv]](https://arxiv.org/abs/2106.01808)  
Giulio Isacchini, Natanael Spisak, Armita Nourmohammad, Thierry Mora, Aleksandra M. Walczak

- **Simulation-Based Inference with Approximately Correct Parameters via Maximum Entropy** [[arXiv]](https://arxiv.org/abs/2104.09668)  
Rainier Barrett, Mehrad Ansari, Gourab Ghoshal, Andrew D White

- **Sequential Neural Posterior and Likelihood Approximation** [[arXiv]](https://arxiv.org/abs/2102.06522)  
Samuel Wiqvist, Jes Frellsen, Umberto Picchini

- **Diagnostics for Conditional Density Models and Bayesian Inference Algorithms** [[arXiv]](https://arxiv.org/abs/2102.10473)  
David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee

- **HNPE: Leveraging Global Parameters for Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2102.06477)  
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort

- **Benchmarking Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2101.04653)  
Jan-Matthis Lueckmann, Jan Boelts, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke

- **Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks** [[arXiv]](https://arxiv.org/abs/2011.05991)  
Niall Jeffrey, Benjamin D. Wandelt

- **Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2011.05836)  
Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe

- **Neural Approximate Sufficient Statistics for Implicit Models** [[arXiv]](https://arxiv.org/abs/2010.10079)  
Yanzhi Chen, Dinghuai Zhang, Michael Gutmann, Aaron Courville, Zhanxing Zhu

- **Amortized Bayesian Model Comparison With Evidential Deep Learning** [[arXiv]](https://arxiv.org/abs/2004.10629)  
Stefan T. Radev, Marco D'Alessandro, Ulf K. Mertens, Andreas Voss, Ullrich Köthe, Paul-Christian Bürkner

- **BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks** [[arXiv]](https://arxiv.org/abs/2003.06281)  
Stefan T. Radev, Ulf K. Mertens, Andreass Voss, Lynton Ardizzone, Ullrich Köthe

- **Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems** [[arXiv]](https://arxiv.org/abs/2002.09301)  
Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig

- **On Contrastive Learning for Likelihood-free Inference** [[arXiv]](https://arxiv.org/abs/2002.03712)  
Conor Durkan, Iain Murray, George Papamakarios

- **Automatic Posterior Transformation for Likelihood-Free Inference** [[arXiv]](https://arxiv.org/abs/1905.07488)  
David S. Greenberg, Marcel Nonnenmacher, Jakob H. Macke

- **Likelihood-free MCMC with Amortized Approximate Ratio Estimators** [[arXiv]](https://arxiv.org/abs/1903.04057)  
Joeri Hermans, Volodimir Begy, Gilles Louppe

- **Dynamic Likelihood-free Inference via Ratio Estimation (DIRE)** [[arXiv]](https://arxiv.org/abs/1810.09899)  
Traiko Dinev, Michael U. Gutmann

- **Analyzing Inverse Problems with Invertible Neural Networks** [[arXiv]](https://arxiv.org/abs/1808.04730)  
Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe

- **Likelihood-free inference with an improved cross-entropy estimator** [[arXiv]](https://arxiv.org/abs/1808.00973)  
Markus Stoye, Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer

- **Mining gold from implicit models to improve likelihood-free inference** [[arXiv]](https://arxiv.org/abs/1805.12244) [[Code]](https://github.com/johannbrehmer/simulator-mining-example)   
Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer

- **Likelihood-free inference with emulator networks** [[arXiv]](https://arxiv.org/abs/1805.09294)  
Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke

- **Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows** [[arXiv]](https://arxiv.org/abs/1805.07226) [[Code]](https://github.com/gpapamak/snl)  
George Papamakarios, David C. Sterratt, Iain Murray

- **A Guide to Constraining Effective Field Theories with Machine Learning** [[arXiv]](https://arxiv.org/abs/1805.00020)  
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez

- **Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation** [[arXiv]](https://arxiv.org/abs/1605.06376)  
George Papamakarios, Iain Murray

- **Approximating Likelihood Ratios with Calibrated Discriminative Classifiers** [[arXiv]](https://arxiv.org/abs/1506.02169)  
Kyle Cranmer, Juan Pavez, Gilles Louppe

# Papers: Application
*Domain application of neural simulation-based inference. Papers listed in reverse-chronological order.*

## Cosmology, Astrophysics, and Astronomy

- **Neural Posterior Estimation with Autoregressive Tiling for Detecting Objects in Astronomical Images** [[arXiv]](https://arxiv.org/abs/2510.03074)
  Jeffrey Regier

- **Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI** [[arXiv]](https://arxiv.org/abs/2507.00514)
  Leander Thiele, Adrian E. Bayer, Naoya Takeishi

- **Simulation-based inference with neural posterior estimation applied to X-ray spectral fitting II -- High-resolution spectroscopy with the X-ray Integral Field Unit** [[arXiv]](https://arxiv.org/abs/2506.05911)
  Simon Dupourqué, Didier Barret

- **Accelerated Bayesian Inference for Pulsar Timing Arrays: Normalizing Flows for Rapid Model Comparison** [[arXiv]](https://arxiv.org/abs/2504.04211)
  Junrong Lai, Changhong Li

- **Robustness of Neural Ratio and Posterior Estimators to Distributional Shifts for Population-Level Dark Matter Analysis** [[arXiv]](https://arxiv.org/abs/2411.05905)
  Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur

- **Robust CMB B-mode analysis with Needlet-ILC and simulation-based inference** [[arXiv]](https://arxiv.org/abs/2512.16869)
  Adriaan J. Duivenvoorden, Kristen Surrao, Adrian E. Bayer, Alexandre E. Adler, Nadia Dachlythra, Susanna Azzoni, J. Colin Hill

- **Simulation-based inference with neural posterior estimation applied to X-ray spectral fitting - III: Deriving exact posteriors with dimension reduction and importance sampling** [[arXiv]](https://arxiv.org/abs/2512.16709)
  Didier Barret, Simon Dupourqué

- **AGN X-ray Reflection Spectroscopy with ML MYTORUS: Neural Posterior Estimation with Training on Observation-Driven Parameter Grids** [[arXiv]](https://arxiv.org/abs/2512.12155)
  Ingrid Vanessa Daza-Perilla, Panayiotis Tzanavaris, V. Madurga-Favieres, M. Yukita, A. Ptak, T. Yaqoob

- **Transformer Embeddings for Fast Microlensing Inference** [[arXiv]](https://arxiv.org/abs/2512.11687)
  Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh

- **Robust and scalable simulation-based inference for gravitational wave signals with gaps** [[arXiv]](https://arxiv.org/abs/2512.18290)
  Ruiting Mao, Jeong Eun Lee, Matthew C. Edwards

- **Vision Transformers for Cosmological Fields: Application to Weak Lensing Mass Maps** [[arXiv]](https://arxiv.org/abs/2512.07125)
  Jash Kakadia, Shubh Agrawal, Kunhao Zhong, Bhuvnesh Jain

- **Black-hole ringdown with templates capturing spin precession: a critical re-analysis of GW190521** [[arXiv]](https://arxiv.org/abs/2512.05193)
  Chiara Anselmo, Costantino Pacilio, Davide Gerosa

- **The dynamical memory of tidal stellar streams: Joint inference of the Galactic potential and the progenitor of GD-1 with flow matching** [[arXiv]](https://arxiv.org/abs/2512.04600)
  Giuseppe Viterbo, Tobias Buck

- **The Shear-to-Cosmology Paradigm I: Hybrid Field-Level and Simulation-Based Framework for Weak Lensing Surveys** [[arXiv]](https://arxiv.org/abs/2511.22851)
  Jiacheng Ding, Chen Su, Ji Yao, Le Zhang, Huanyuan Shan

- **Modeling X-ray photon pile-up with a normalizing flow** [[arXiv]](https://arxiv.org/abs/2511.11863)
  Ole König, Daniela Huppenkothen, Douglas Finkbeiner, Christian Kirsch, Jörn Wilms, Justina R. Yang, James F. Steiner, Juan Rafael Martínez-Galarza

- **Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer** [[arXiv]](https://arxiv.org/abs/2511.10640)
  Thomas Harvey, Christopher C. Lovell, Sophie Newman, Christopher J. Conselice, et al.

- **Accelerated inference of microlensed gravitational waves with machine learning** [[arXiv]](https://arxiv.org/abs/2511.08486)
  Marienza Caldarola, Srashti Goyal, Nihar Gupte, Stephen R. Green, Miguel Zumalacárregui

- **Dark Energy Survey Year 3 results: Simulation-based wCDM inference from weak lensing and galaxy clustering maps with deep learning. I. Analysis design** [[arXiv]](https://arxiv.org/abs/2511.04681)
  A. Thomsen, J. Bucko, T. Kacprzak, V. Ajani, J. Fluri, A. Refregier, et al.

- **Quantifying Weighted Morphological Content of Large-Scale Structures via Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2511.03636)
  M. H. Jalali Kanafi, S. M. S. Movahed

- **Reliable Parameter Inference for the Epoch of Reionization using Balanced Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2511.02808)
  Diego González-Hernández, Molly Wolfson, Joseph F. Hennawi

- **LyαNNA II: Field-level inference with noisy Lyα forest spectra** [[arXiv]](https://arxiv.org/abs/2510.19899)
  Parth Nayak, Michael Walther, Daniel Gruen

- **Neural Posterior Estimation for White Dwarf Spectroscopic Characterization** [[arXiv]](https://arxiv.org/abs/2510.16261)
  Olivier Vincent, Patrick Dufour, Pierre Bergeron

- **Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties** [[arXiv]](https://arxiv.org/abs/2510.14202)
  Edgar P. Vidal, Alexander T. Gagliano, Carolina Cuesta-Lazaro

- **Extracting cosmological information from the abundance of galaxy clusters with simulation-based inference** [[arXiv]](https://arxiv.org/abs/2504.10230)
  Íñigo Zubeldia, Boris Bolliet, Anthony Challinor, William Handley

- **Trial by FIRE: Probing the dark matter density profile of dwarf galaxies with GraphNPE** [[arXiv]](https://arxiv.org/abs/2503.03812)  
  Tri Nguyen, Justin Read, Lina Necib, Siddharth Mishra-Sharma, Claude-André Faucher-Giguère, Andrew Wetzel

- **How many simulations do we need for simulation-based inference in cosmology?** [[arXiv]](https://arxiv.org/abs/2503.13755)  
  Anirban Bairagi, Benjamin D. Wandelt, Francisco Villaescusa-Navarro

- **Fast Sampling of Cosmological Initial Conditions with Gaussian Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2502.03139)  
  Oleg Savchenko, Guillermo Franco Abellán, Florian List, Noemi Anau Montel, Christoph Weniger

- **Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulators** [[arXiv]](https://arxiv.org/abs/2411.14748)  
  He Jia

- **Hybrid Summary Statistics** [[arXiv]](https://arxiv.org/abs/2410.07548)  
  T. Lucas Makinen, Ce Sui, Benjamin D. Wandelt, Natalia Porqueres, Alan Heavens

- **What to do when things get crowded? Scalable joint analysis of overlapping gravitational wave signals** [[arXiv]](https://arxiv.org/abs/2308.06318)  
  James Alvey, Uddipta Bhardwaj, Samaya Nissanke, Christoph Weniger

- **Leveraging Time-Dependent Instrumental Noise for LISA SGWB Analysis** [[arXiv]](https://arxiv.org/abs/2408.00832)  
  James Alvey, Uddipta Bhardwaj, Valerie Domcke, Mauro Pieroni, Christoph Weniger

- **Rapid Likelihood Free Inference of Compact Binary Coalescences using Accelerated Hardware** [[arXiv]](https://arxiv.org/abs/2407.19048)  
  Deep Chatterjee et al

- **Kilonova Light Curve Parameter Estimation Using Likelihood-Free Inference** [[arXiv]](https://arxiv.org/abs/2408.06947)  
  Malina Desai, Deep Chatterjee, Sahil Jhawar, Philip Harris, Erik Katsavounidis, Michael Coughlin

- **Learning Optimal and Interpretable Summary Statistics of Galaxy Catalogs with SBI** [[arXiv]](https://arxiv.org/abs/2411.08957)  
  Kai Lehman, Sven Krippendorf, Jochen Weller, Klaus Dolag

- **Simulation-based inference of the 2D ex-situ stellar mass fraction distribution of galaxies using variational autoencoders** [[arXiv]](https://arxiv.org/abs/2410.24069)  
  Eirini Angeloudi et al

- **Constraining the dispersion measure redshift relation with simulation-based inference** [[arXiv]](https://arxiv.org/abs/2410.07084)  
  Koustav Konar, Robert Reischke, Steffen Hagstotz, Andrina Nicola, Hendrik Hildebrandt

- **Reconstructing galaxy star formation histories from COSMOS2020 photometry using simulation-based inference** [[arXiv]](https://arxiv.org/abs/2410.00795)  
  G. Aufort et al

- **Constraining Cosmology with Simulation-based inference and Optical Galaxy Cluster Abundance** [[arXiv]](https://arxiv.org/abs/2409.20507)  
  Moonzarin Reza, Yuanyuan Zhang, Camille Avestruz, Louis E. Strigari, Simone Shevchuk, Francisco Villaescusa-Navarro

- **Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2407.17292)  
  Sreevani Jarugula, Brian Nord, Abhijith Gandrakota, Aleksandra Ćiprijanović

- **Accounting for Selection Effects in Supernova Cosmology with Simulation-Based Inference and Hierarchical Bayesian Modelling** [[arXiv]](https://arxiv.org/abs/2407.15923)  
  Benjamin M. Boyd, Matthew Grayling, Stephen Thorp, Kaisey S. Mandel

- **Fast and Flexible Inference Framework for Continuum Reverberation Mapping using Simulation-based Inference with Deep Learning** [[arXiv]](https://arxiv.org/abs/2407.14621)  
  Jennifer I-Hsiu Li et al

- **Optimal Neural Summarisation for Full-Field Weak Lensing Cosmological Implicit Inference** [[arXiv]](https://arxiv.org/abs/2407.10877)  
  Denise Lanzieri et al

- **ABCMB: Deep Delensing Assisted Likelihood-Free Inference from CMB Polarization Maps** [[arXiv]](https://arxiv.org/abs/2407.10013)  
  Kai Yi, Yanan Fan, Jan Hamann, Pietro Liò, Yuguang Wang

- **Silkscreen: Direct Measurements of Galaxy Distances from Survey Image Cutouts** [[arXiv]](https://arxiv.org/abs/2407.04091)  
  Tim B. Miller, Imad Pasha, Ava Polzin, Pieter van Dokkum

- **Deriving the star formation histories of galaxies from spectra with simulation-based inference** [[arXiv]](https://arxiv.org/abs/2406.18661)  
  Patricia Iglesias-Navarro et al

- **Constraining Cosmological Parameters with Needlet Internal Linear Combination Maps II: Likelihood-Free Inference on NILC Power Spectra** [[arXiv]](https://arxiv.org/abs/2406.16811)  
  Kristen M. Surrao, J. Colin Hill

- **Simulation-based Inference for Gravitational-waves from Intermediate-Mass Binary Black Holes in Real Noise** [[arXiv]](https://arxiv.org/abs/2406.03935)  
  Vivien Raymond, Sama Al-Shammari, Alexandre Göttel

- **Simulation-based inference of radio millisecond pulsars in globular clusters** [[arXiv]](https://arxiv.org/abs/2405.15691)  
  Joanna Berteaud, Christopher Eckner, Francesca Calore, Maïca Clavel, Daryl Haggard

- **Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours** [[arXiv]](https://arxiv.org/abs/2411.13960)  
  Christopher C. Lovell et al

- **Combining summary statistics with simulation-based inference for the 21 cm signal from the Epoch of Reionization** [[arXiv]](https://arxiv.org/abs/2411.14419)  
  Benoit Semelin, Romain Mériot, Ashutosh Mishra, David Cornu

- **Domain-Adaptive Neural Posterior Estimation for Strong Gravitational Lens Analysis** [[arXiv]](https://arxiv.org/abs/2410.16347)  
  Paxson Swierc, Marcos Tamargo-Arizmendi, Aleksandra Ćiprijanović, Brian D. Nord

- **Mean-Field Simulation-Based Inference for Cosmological Initial Conditions** [[arXiv]](https://arxiv.org/abs/2410.15808)  
  Oleg Savchenko, Florian List, Guillermo Franco Abellán, Noemi Anau Montel, Christoph Weniger

- **Field-level cosmological model selection: field-level simulation-based inference for Stage IV cosmic shear can distinguish dynamical dark energy** [[arXiv]](https://arxiv.org/abs/2410.10616)  
  A. Spurio Mancini, K. Lin, J. D. McEwen

- **Simulation-Based Inference Benchmark for LSST Weak Lensing Cosmology** [[arXiv]](https://arxiv.org/abs/2409.17975)  
  Justine Zeghal et al

- **Cosmology from HSC Y1 Weak Lensing with Combined Higher-Order Statistics and Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2409.01301)  
  Camila P. Novaes et al

- **Fisher's Mirage: Noise Tightening of Cosmological Constraints in Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2406.06067)  
  Christopher Wilson, Rachel Bean

- **Efficient Massive Black Hole Binary parameter estimation for LISA using Sequential Neural Likelihood** [[arXiv]](https://arxiv.org/abs/2406.00565)
  Iván Martín Vílchez, Carlos F. Sopuerta

- **Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps II. Cosmological results** [[arXiv]](https://arxiv.org/abs/2405.10881)  
  M. Gatti, G. Campailla, N. Jeffrey, L. Whiteway, A. Porredon, J. Prat, J. Williamson, M. Raveri, B. Jain, V. Ajani, C. Zhou, J. Blazek, D. Anbajagane, S. Samuroff, T. Kacprzak, A. Alarcon, A. Amon, K. Bechtol, M. Becker, G. Bernstein, A. Campos, C. Chang, R. Chen

- **A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics** [[arXiv]](https://arxiv.org/abs/2405.02252)  
  Beyond-2pt Collaboration, :, Elisabeth Krause, Yosuke Kobayashi, Andrés N. Salcedo, Mikhail M. Ivanov, Tom Abel, Kazuyuki Akitsu, Raul E. Angulo, Giovanni Cabass, Sofia Contarini, Carolina Cuesta-Lazaro, ChangHoon Hahn, Nico Hamaus, Donghui Jeong, Chirag Modi, Nhat-Minh Nguyen, Takahiro Nishimichi, Enrique Paillas, Marcos Pellejero Ibañez, Oliver H. E. Philcox, Alice Pisani, Fabian Schmidt, Satoshi Tanaka, Giovanni Verza

- **KiDS-SBI: Simulation-Based Inference Analysis of KiDS-1000 Cosmic Shear** [[arXiv]](https://arxiv.org/abs/2404.15402)  
  Maximilian von Wietersheim-Kramsta, Kiyam Lin, Nicolas Tessore, Benjamin Joachimi, Arthur Loureiro, Robert Reischke, Angus H. Wright

- **A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods** [[arXiv]](https://arxiv.org/abs/2404.14487)  
  Sebastian Wagner-Carena, Jaehoon Lee, Jeffrey Pennington, Jelle Aalbers, Simon Birrer, Risa H. Wechsler

- **Simulation-based inference of black hole ringdowns in the time domain** [[arXiv]](https://arxiv.org/abs/2404.11373)  
  Costantino Pacilio, Swetha Bhagwat, Roberto Cotesta

- **How much information can be extracted from galaxy clustering at the field level?** [[arXiv]](https://arxiv.org/abs/2403.03220)  
  Nhat-Minh Nguyen, Fabian Schmidt, Beatriz Tucci, Martin Reinecke, Andrija Kostić

- **SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data** [[arXiv]](https://arxiv.org/abs/2403.07871)  
  Konstantin Karchev, Matthew Grayling, Benjamin M. Boyd, Roberto Trotta, Kaisey S. Mandel, Christoph Weniger

- **Tuning neural posterior estimation for gravitational wave inference** [[arXiv]](https://arxiv.org/abs/2403.02443)  
  Alex Kolmus, Justin Janquart, Tomasz Baka, Twan van Laarhoven, Chris Van Den Broeck, Tom Heskes

- **Dark Energy Survey Year 3 results: likelihood-free, simulation-based wCDM inference with neural compression of weak-lensing map statistics** [[arXiv]](https://arxiv.org/abs/2403.02314)  
  N. Jeffrey, L. Whiteway, M. Gatti, J. Williamson, J. Alsing, A. Porredon, J. Prat, C. Doux, B. Jain, C. Chang, T. -Y. Cheng, T. Kacprzak, P. Lemos, A. Alarcon, A. Amon, K. Bechtol, M. R. Becker, G. M. Bernstein, A. Campos, A. Carnero Rosell, R. Chen, A. Choi, J. DeRose, A. Drlica-Wagner, K. Eckert

- **Simulation-Based Inference of the sky-averaged 21-cm signal from CD-EoR with REACH** [[arXiv]](https://arxiv.org/abs/2403.14618)  
  Anchal Saxena, P. Daniel Meerburg, Christoph Weniger, Eloy de Lera Acedo, Will Handley

- **Exploring the role of the halo mass function for inferring astrophysical parameters during reionisation** [[arXiv]](https://arxiv.org/abs/2403.14061)  
  Bradley Greig, David Prelogović, Jordan Mirocha, Yuxiang Qin, Yuan-Sen Ting, Andrei Mesinger

- **SimBIG: Cosmological Constraints using Simulation-Based Inference of Galaxy Clustering with Marked Power Spectra** [[arXiv]](https://arxiv.org/abs/2404.04228)  
  Elena Massara, ChangHoon Hahn, Michael Eickenberg, Shirley Ho, Jiamin Hou, Pablo Lemos, Chirag Modi, Azadeh Moradinezhad Dizgah, Liam Parker, Bruno Régaldo-Saint Blancard

- **Inferring astrophysical parameters using the 2D cylindrical power spectrum from reionisation** [[arXiv]](https://arxiv.org/abs/2403.14060)  
  Bradley Greig, David Prelogović, Yuxiang Qin, Yuan-Sen Ting, Andrei Mesinger

- **Fast likelihood-free inference in the LSS Stage IV era** [[arXiv]](https://arxiv.org/abs/2403.14750)  
  Guillermo Franco Abellán, Guadalupe Cañas Herrera, Matteo Martinelli, Oleg Savchenko, Davide Sciotti, Christoph Weniger

- **Simulation-based Bayesian inference of protoplanetary disk winds from forbidden line profiles** [[arXiv]](https://arxiv.org/abs/2403.10243)  
  Ahmad Nemer, ChangHoon Hahn, Jiaxuan Li, Peter Melchior, Jeremy Goodman

- **Neural Simulation-Based Inference of the Neutron Star Equation of State directly from Telescope Spectra** [[arXiv]](https://arxiv.org/abs/2403.00287)  
  Len Brandes, Chirag Modi, Aishik Ghosh, Delaney Farrell, Lee Lindblom, Lukas Heinrich, Andrew W. Steiner, Fridolin Weber, Daniel Whiteson

- **Applying Simulation-Based Inference to Spectral and Spatial Information from the Galactic Center Gamma-Ray Excess** [[arXiv]](https://arxiv.org/abs/2402.04549)  
Katharena Christy, Eric J. Baxter, Jason Kumar

- **SIMBIG : Cosmological Constraints from the Redshift-Space Galaxy Skew Spectra** [[arXiv]](https://arxiv.org/abs/2401.15074)  
Jiamin Hou, Azadeh Moradinezhad Dizgah, ChangHoon Hahn, Michael Eickenberg, Shirley Ho, Pablo Lemos, Elena Massara, Chirag Modi, Liam Parker, Bruno Régaldo-Saint Blancard

- **Inferring galaxy cluster masses from cosmic microwave background lensing with neural simulation based inference** [[arXiv]](https://arxiv.org/abs/2401.08910)  
Eric J. Baxter, Shivam Pandey

- **Simulation-based inference of deep fields: galaxy population model and redshift distributions** [[arXiv]](https://arxiv.org/abs/2401.06846)  
Beatrice Moser, Tomasz Kacprzak, Silvan Fischbacher, Alexandre Refregier, Dominic Grimm, Luca Tortorelli

- **Simulation-Based Inference with Neural Posterior Estimation applied to X-ray spectral fitting: Demonstration of working principles down to the Poisson regime** [[arXiv]](https://arxiv.org/abs/2401.06061)  
Didier Barret, Simon Dupourqué

- **Optimal, fast, and robust inference of reionization-era cosmology with the 21cmPIE-INN** [[arXiv]](https://arxiv.org/abs/2401.04174)  
Benedikt Schosser, Caroline Heneka, Tilman Plehn

- **Isolated Pulsar Population Synthesis with Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2312.14848)  
Vanessa Graber, Michele Ronchi, Celsa Pardo-Araujo, Nanda Rea

- **Constraints on the Evolution of the Ionizing Background and Ionizing Photon Mean Free Path at the End of Reionization** [[arXiv]](https://arxiv.org/abs/2312.08464)  
Frederick B. Davies et al

- **Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling** [[arXiv]](https://arxiv.org/abs/2312.08295)  
Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf

- **Efficient Parameter Inference for Gravitational Wave Signals in the Presence of Transient Noises Using Normalizing Flow** [[arXiv]](https://arxiv.org/abs/2312.08122)  
Tian-Yang Sun, Chun-Yu Xiong, Shang-Jie Jin, Yu-Xin Wang, Jing-Fei Zhang, Xin Zhang

- **Optimizing Likelihood-Free Inference using Self-Supervised Neural Symmetry Embeddings** [[arXiv]](https://arxiv.org/abs/2312.07615)  
Deep Chatterjee, Philip C. Harris, Maanas Goel, Malina Desai, Michael W. Coughlin, Erik Katsavounidis

- **Learning Reionization History from Quasars with Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2311.16238)  
Huanqing Chen, Joshua Speagle, Keir K. Rogers

- **Simulation Based Inference of BNS Kilonova Properties: A Case Study with AT2017gfo** [[arXiv]](https://arxiv.org/abs/2311.09471)  
Phelipe A. Darc, Clecio R. Bom, Bernardo M. O. Fraga, Charlie D. Kilpatrick

- **Bayesian Simulation-based Inference for Cosmological Initial Conditions** [[arXiv]](https://arxiv.org/abs/2310.19910)  
Florian List, Noemi Anau Montel, Christoph Weniger

- **Simulation-based Inference of Reionization Parameters from 3D Tomographic 21 cm Light-cone Images -- II: Application of Solid Harmonic Wavelet Scattering Transform** [[arXiv]](https://arxiv.org/abs/2310.17602)  
Xiaosheng Zhao, Yi Mao, Shifan Zuo, Benjamin D. Wandelt

- **Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps I: validation on simulations** [[arXiv]](https://arxiv.org/abs/2310.17557)  
M. Gatti, N. Jeffrey, L. Whiteway, J. Williamson, B. Jain, V. Ajani, D. Anbajagane, G. Giannini, C. Zhou, A. Porredon, J. Prat, M. Yamamoto, J. Blazek, T. Kacprzak, S. Samuroff, A. Alarcon, A. Amon, K. Bechtol, M. Becker, G. Bernstein, A. Campos, C. Chang, R. Chen, A. Choi, C. Davis , et al.

- **SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering** [[arXiv]](https://arxiv.org/abs/2310.15256)  
Pablo Lemos, Liam Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg, Jiamin Hou, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Bruno Regaldo-Saint Blancard, David Spergel

- **SIMBIG: Galaxy Clustering Analysis with the Wavelet Scattering Transform** [[arXiv]](https://arxiv.org/abs/2310.15250)  
Bruno Régaldo-Saint Blancard, ChangHoon Hahn, Shirley Ho, Jiamin Hou, Pablo Lemos, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Liam Parker, Yuling Yao, Michael Eickenberg

- **SIMBIG: The First Cosmological Constraints from the Non-Linear Galaxy Bispectrum** [[arXiv]](https://arxiv.org/abs/2310.15243)  
ChangHoon Hahn, Michael Eickenberg, Shirley Ho, Jiamin Hou, Pablo Lemos, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Liam Parker, Bruno Régaldo-Saint Blancard

- **Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects** [[arXiv]](https://arxiv.org/abs/2310.15234)  
Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez, Tiago Castro, Yueying Ni, Christopher C. Lovell, Elena Hernandez-Martinez, Federico Marinacci, David N. Spergel, Klaus Dolag, Lars Hernquist, Mark Vogelsberger

- **HaloFlow I: Neural Inference of Halo Mass from Galaxy Photometry and Morphology** [[arXiv]](https://arxiv.org/abs/2310.04503)  
ChangHoon Hahn, Connor Bottrell, Khee-Gan Lee

- **EFTofLSS meets simulation-based inference: σ8 from biased tracers** [[arXiv]](https://arxiv.org/abs/2310.03741)  
Beatriz Tucci, Fabian Schmidt

- **Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering** [[arXiv]](https://arxiv.org/abs/2309.15071)  
Chirag Modi, Shivam Pandey, Matthew Ho, ChangHoon Hahn, Bruno Regaldo-Saint Blancard, Benjamin Wandelt

- **Hybrid SBI or How I Learned to Stop Worrying and Learn the Likelihood** [[arXiv]](https://arxiv.org/abs/2309.10270)  
Chirag Modi, Oliver H. E. Philcox

- **Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows** [[arXiv]](https://arxiv.org/abs/2309.07954)  
Mayeul Aubin et al

- **Simulation-based inference for stochastic gravitational wave background data analysis** [[arXiv]](https://arxiv.org/abs/2309.09337)
  James Alvey, Uddipta Bhardwaj, Valerie Domcke, Mauro Pieroni, Christoph Weniger

- **Neural Posterior Estimation with guaranteed exact coverage: the ringdown of GW150914** [[arXiv]](https://arxiv.org/abs/2305.18528)  
Marco Crisostomi, Kallol Dey, Enrico Barausse, Roberto Trotta

- **The likelihood of the 21-cm power spectrum** [[arXiv]](https://arxiv.org/abs/2305.03074)  
David Prelogović, Andrei Mesinger

- **The angular power spectrum of gravitational-wave transient sources as a probe of the large-scale structure** [[arXiv]](https://arxiv.org/abs/2305.02652)  
Yanyan Zheng, Nikolaos Kouvatsos, Jacob Golomb, Marco Cavaglià, Arianna I. Renzini, Mairi Sakellariadou

- **SBI++: Flexible, Ultra-fast Likelihood-free Inference Customized for Astronomical Application** [[arXiv]](https://arxiv.org/abs/2304.05281)  
Bingjie Wang, Joel Leja, V. Ashley Villar, Joshua S. Speagle

- **Peregrine: Sequential simulation-based inference for gravitational wave signals** [[arXiv]](https://arxiv.org/abs/2304.02035)  
Uddipta Bhardwaj, James Alvey, Benjamin Kurt Miller, Samaya Nissanke, Christoph Weniger

- **Albatross: A scalable simulation-based inference pipeline for analysing stellar streams in the Milky Way** [[arXiv]](https://arxiv.org/abs/2304.02032)  
James Alvey, Mathis Gerdes, Christoph Weniger

- **Investigating the turbulent hot gas in X-COP galaxy clusters** [[arXiv]](https://arxiv.org/abs/2303.15102)  
Simon Dupourqué, Nicolas Clerc, Etienne Pointecouteau, Dominique Eckert, Stefano Ettori, Franco Vazza

- **Constraining the X-ray heating and reionization using 21-cm power spectra with Marginal Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2303.07339)  
Anchal Saxena, Alex Cole, Simon Gazagnes, P. Daniel Meerburg, Christoph Weniger, Samuel J. Witte

- **Neural posterior estimation for exoplanetary atmospheric retrieval** [[arXiv]](https://arxiv.org/abs/2301.06575)  
Malavika Vasist, François Rozet, Olivier Absil, Paul Mollière, Evert Nasedkin, Gilles Louppe

- **Debiasing Standard Siren Inference of the Hubble Constant with Marginal Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2301.05241)  
Samuel Gagnon-Hartman, John Ruan, Daryl Haggard

- **Calibrating cosmological simulations with implicit likelihood inference using galaxy growth observables** [[arXiv]](https://arxiv.org/abs/2211.16461)  
Yongseok Jo et al

- **DIGS: Deep Inference of Galaxy Spectra with Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2211.09126)  
Gourav Khullar, Brian Nord, Aleksandra Ciprijanovic, Jason Poh, Fei Xu

- **Detection is truncation: studying source populations with truncated marginal neural ratio estimation** [[arXiv]](https://arxiv.org/abs/2211.04291)  
Noemi Anau Montel, Christoph Weniger

- **SIMBIG : A Forward Modeling Approach To Analyzing Galaxy Clustering** [[arXiv]](https://arxiv.org/abs/2211.00723)  
ChangHoon Hahn et al

- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference** [[arXiv]](https://arxiv.org/abs/2210.05686)  
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

- **One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses** [[arXiv]](https://arxiv.org/abs/2209.09918)  
Adam Coogan, Noemi Anau Montel, Konstantin Karchev, Meiert W. Grootes, Francesco Nattino, Christoph Weniger

- **SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation** [[arXiv]](https://arxiv.org/abs/2209.06733)  
Konstantin Karchev, Roberto Trotta, Christoph Weniger

- **Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation** [[arXiv]](https://arxiv.org/abs/2208.13796)  
Gemma Zhang, Siddharth Mishra-Sharma, Cora Dvorkin

- **Uncovering dark matter density profiles in dwarf galaxies with graph neural networks** [[arXiv]](https://arxiv.org/abs/2208.12825)  
Tri Nguyen, Siddharth Mishra-Sharma, Reuel Williams, Lina Necib

- **Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2208.00134)  
Moonzarin Reza, Yuanyuan Zhang, Brian Nord, Jason Poh, Aleksandra Ciprijanovic, Louis Strigari

- **Neural Posterior Estimation with Differentiable Simulators** [[arXiv]](https://arxiv.org/abs/2207.05636)  
Justine Zeghal, François Lanusse, Alexandre Boucaud, Benjamin Remy, Eric Aubourg

- **Towards reconstructing the halo clustering and halo mass function of N-body simulations using neural ratio estimation** [[arXiv]](https://arxiv.org/abs/2206.11312)  
Androniki Dimitriou, Christoph Weniger, Camila A. Correa

- **Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation** [[arXiv]](https://arxiv.org/abs/2205.09126)  
Noemi Anau Montel, Adam Coogan, Camila Correa, Konstantin Karchev, Christoph Weniger

- **Implicit Likelihood Inference of Reionization Parameters from the 21 cm Power Spectrum** [[arXiv]](https://arxiv.org/abs/2203.15734)  
Xiaosheng Zhao, Yi Mao, Benjamin D. Wandelt

- **Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2203.07391)  
ChangHoon Hahn, Peter Melchior

- **Simulation-Based Inference of Strong Gravitational Lensing Parameters** [[arXiv]](https://arxiv.org/abs/2112.05278)  
Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur, Benjamin Wandelt

- **Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation** [[arXiv]](https://arxiv.org/abs/2111.08030)  
Alex Cole, Benjamin Kurt Miller, Samuel J. Witte, Maxwell X. Cai, Meiert W. Grootes, Francesco Nattino, Christoph Weniger

- **A neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess** [[arXiv]](https://arxiv.org/abs/2110.06931)  
Siddharth Mishra-Sharma, Kyle Cranmer

- **Inferring dark matter substructure with astrometric lensing beyond the power spectrum** [[arXiv]](https://arxiv.org/abs/2110.01620)  
Siddharth Mishra-Sharma

- **Approximate Bayesian Neural Doppler Imaging** [[arXiv]](https://arxiv.org/abs/2108.09266)  
A. Asensio Ramos, C. Diaz Baso, O. Kochukhov

- **Lossless, Scalable Implicit Likelihood Inference for Cosmological Fields** [[arXiv]](https://arxiv.org/abs/2107.07405)  
T. Lucas Makinen, Tom Charnock, Justin Alsing, Benjamin D. Wandelt

- **Real-time gravitational-wave science with neural posterior estimation** [[arXiv]](https://arxiv.org/abs/2106.12594)  
Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf

- **Real-Time Likelihood-Free Inference of Roman Binary Microlensing Events with Amortized Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2102.05673)  
Keming Zhang, Joshua S. Bloom, B. Scott Gaudi, Francois Lanusse, Casey Lam, Jessica R. Lu

- **Towards constraining warm dark matter with stellar streams through neural simulation-based inference** [[arXiv]](https://arxiv.org/abs/2011.14923)  
Joeri Hermans, Nilanjan Banik, Christoph Weniger, Gianfranco Bertone, Gilles Louppe

- **Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization** [[arXiv]](https://arxiv.org/abs/2010.12931)  
Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke, Christoph Weniger, Andrew R. Williamson, Gilles Louppe

- **The sum of the masses of the Milky Way and M31: a likelihood-free inference approach** [[arXiv]](https://arxiv.org/abs/2010.08537)  
Pablo Lemos, Niall Jeffrey, Lorne Whiteway, Ofer Lahav, Niam I Libeskind, Yehuda Hoffman

- **Likelihood-free inference with neural compression of DES SV weak lensing map statistics** [[arXiv]](https://arxiv.org/abs/2009.08459)  
Niall Jeffrey, Justin Alsing, François Lanusse

- **Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning** [[arXiv]](https://arxiv.org/abs/1909.02005)  
Johann Brehmer, Siddharth Mishra-Sharma, Joeri Hermans, Gilles Louppe, Kyle Cranmer

- **Fast likelihood-free cosmology with neural density estimators and active learning** [[arXiv]](https://arxiv.org/abs/1903.00007)  
Justin Alsing, Tom Charnock, Stephen Feeney, Benjamin Wandelt

## Particle Physics

- **Machine Learning-Informed 3+1 Sterile Neutrino Global Fits using Posterior Density Estimation of Electron Disappearance Data** [[arXiv]](https://arxiv.org/abs/2512.05784)
  Joshua Villarreal, Julia Woodward, John Hardin, Janet Conrad

- **Advancing Tools for Simulation-Based Inference** [[arXiv]](https://arxiv.org/abs/2410.07315)
  Henning Bahl, Victor Bresó, Giovanni De Crescenzo, Tilman Plehn

- **Constraining the Higgs Potential with Neural Simulation-based Inference for Di-Higgs Production** [[arXiv]](https://arxiv.org/abs/2405.15847)
  Radha Mastandrea, Benjamin Nachman, Tilman Plehn

- **Simulation-based inference in the search for CP violation in leptonic WH production** [[arXiv]](https://arxiv.org/abs/2308.02882)  
Ricardo Barrué, Patricia Conde-Muíño, Valerio Dao, Rui Santos

- **Reconstructing axion-like particles from beam dumps with simulation-based inference** [[arXiv]](https://arxiv.org/abs/2308.01353)  
Alessandro Morandini, Torben Ferber, Felix Kahlhoefer

- **Measuring QCD Splittings with Invertible Networks** [[arXiv]](https://arxiv.org/abs/2012.09873)  
Sebastian Bieringer, Anja Butter, Theo Heimel, Stefan Höche, Ullrich Köthe, Tilman Plehn, Stefan T. Radev

- **Simulation-based inference methods for particle physics** [[arXiv]](https://arxiv.org/abs/2010.06439)  
Johann Brehmer, Kyle Cranmer

- **MadMiner: Machine learning-based inference for particle physics** [[arXiv]](https://arxiv.org/abs/1907.10621)  
Johann Brehmer, Felix Kling, Irina Espejo, Kyle Cranmer

- **Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale** [[arXiv]](https://arxiv.org/abs/1907.03382)  
Atılım Güneş Baydin et al

- **Constraining Effective Field Theories with Machine Learning** [[arXiv]](https://arxiv.org/abs/1805.00013)  
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez

## Neuroscience and Cognitive Science

- **Approximation of Intractable Likelihood Functions in Systems Biology via Normalizing Flows** [[arXiv]](https://arxiv.org/abs/2312.02391)  
Vincent D. Zaballa, Elliot E. Hui

- **Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2023.04.17.537118v1.abstract)  
Nicholas Tolley, Pedro L. C. Rodrigues, Alexandre Gramfort, Stephanie Jones

- **A General Integrative Neurocognitive Modeling Framework to Jointly Describe EEG and Decision-making on Single Trials** [[Paper]](https://link.springer.com/article/10.1007/s42113-023-00167-4)  
Amin Ghaderi-Kangavari, Jamal Amani Rad, Michael D. Nunez

- **Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware** [[arXiv]](https://arxiv.org/abs/2303.16056)  
Jakob Kaiser, Raphael Stock, Eric Müller, Johannes Schemmel, Sebastian Schmitt

- **Simulation-based inference for efficient identification of generative models in computational connectomics** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1.abstract)  
Jan Boelts, Philipp Harth, Richard Gao, Daniel Udvary, Felipe Yáñez, Daniel Baum, Hans-Christian Hege, Marcel Oberlaender, Jakob H. Macke

- **Likelihood approximation networks (LANs) for fast inference of simulation models in cognitive neuroscience** [[Paper]](https://elifesciences.org/articles/65074)  
Alexander Fengler, Lakshmi N Govindarajan, Tony Chen, Michael J Frank

- **Training deep neural density estimators to identify mechanistic models of neural dynamics** [[Paper]](https://elifesciences.org/articles/56261)  
Pedro J Gonçalves et al

- **Mental speed is high until age 60 as revealed by analysis of over a million participants** [[Paper]](https://www.nature.com/articles/s41562-021-01282-7)  
Mischa von Krause, Stefan T. Radev, Andreas Voss

- **Amortized Bayesian Inference for Models of Cognition** [[arXiv]](https://arxiv.org/abs/2005.03899)  
Stefan T. Radev, Andreas Voss, Eva Marie Wieschen, Paul-Christian Bürkner

## Health and Medicine

- **Simulation-Based Inference of Developmental EEG Maturation with the Spectral Graph Model** [[arXiv]](https://arxiv.org/abs/2405.02524)  
  Danilo Bernardo, Xihe Xie, Parul Verma, Jonathan Kim, Virginia Liu, Ye Wu, Pew-Thian Yap, Srikantan Nagarajan, Ashish Raj

- **AI-powered simulation-based inference of a genuinely spatial-stochastic model of early mouse embryogenesis** [[arXiv]](https://arxiv.org/abs/2402.15330)  
  Michael A. Ramirez-Sierra, Thomas R. Sokolowski

- **Modeling the Age Pattern of Fertility: An Individual-Level Approach** [[arXiv]](https://arxiv.org/abs/2312.08185)  
Daniel Ciganda, Nicolas Todd

- **Simulation-based Inference for Cardiovascular Models** [[arXiv]](https://arxiv.org/abs/2307.13918)    
Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen

- **Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2023.01.09.523230v1.abstract)  
Itamar Caspi, Moran Meir, Nadav Ben Nun, Uri Yakhini, Adi Stern,  Yoav Ram

- **Simulation-Based Inference for Whole-Brain Network Modeling of Epilepsy using Deep Neural Density Estimators** [[medRxiv]](https://www.medrxiv.org/content/10.1101/2022.06.02.22275860v1)  
Meysam Hashemi, Anirudh N. Vattikonda, Jayant Jha, Viktor Sip, Marmaduke M. Woodman, Fabrice Bartolomei, Viktor K. Jirsa

- **OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany** [[arXiv]](https://arxiv.org/abs/2010.00300)  
Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa M. Eichel, Till Bärnighausen, Ullrich Köthe

- **Simulation-Based Inference for Global Health Decisions** [[arXiv]](https://arxiv.org/abs/2005.07062)  
Christian Schroeder de Witt et al

## Other Domains
*Applications where multiple papers could not be grouped under a single heading.*

- **Simulation-Based Inference of Cell Migration Dynamics in Complex Spatial Environments** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2025.09.25.678460v1)
  Jonas Arruda, Emad Alamoudi, Robert Mueller, Marc Vaisband, Ronja Molkenbur, Jack Merrin, Eva Kiermaier, Jan Hasenauer

- **Simulation-Based Inference of Ginzburg--Landau Parameters in Type--1.5 Superconductors** [[arXiv]](https://arxiv.org/abs/2512.02411)
  Jung-Shen Kao

- **Modeling multi-agent motion dynamics in immersive rooms** [[arXiv]](https://arxiv.org/abs/2511.08763)
  Jerry M. Huang, Stefan T. Radev

- **From Observations to Parameters: Detecting Changepoint in Nonlinear Dynamics with Simulation-based Inference** [[arXiv]](https://arxiv.org/abs/2510.17933)
  Xiangbo Deng, Cheng Chen, Peng Yang

- **Simulation-based inference of single-molecule experiments** [[arXiv]](https://arxiv.org/abs/2410.15896)  
  Lars Dingeldein, Pilar Cossio, Roberto Covino

- **Full-waveform earthquake source inversion using simulation-based inference** [[arXiv]](https://arxiv.org/abs/2410.23238)  
  A. A. Saoulis, D. Piras, A. Spurio Mancini, B. Joachimi, A. M. G. Ferreira

- **Fast and Reliable Probabilistic Reflectometry Inversion with Prior-Amortized Neural Posterior Estimation** [[arXiv]](https://arxiv.org/abs/2407.18648)  
  Vladimir Starostin et al

- **A Comprehensive Guide to Simulation-based Inference in Computational Biology** [[arXiv]](https://arxiv.org/abs/2409.19675)  
  Xiaoyu Wang, Ryan P. Kelly, Adrianne L. Jenner, David J. Warne, Christopher Drovandi

- **SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences** [[arXiv]](https://arxiv.org/abs/2404.16590)  
  Samuel Stockman, Daniel J. Lawson, Maximilian J. Werner

- **Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers** [[arXiv]](https://arxiv.org/abs/2312.02997)  
Guy Moss, Vjeran Višnjević, Olaf Eisen, Falk M. Oraschewski, Cornelius Schröder, Jakob H. Macke, Reinhard Drews

- **Amortized Bayesian Decision Making for simulation-based models** [[arXiv]](https://arxiv.org/abs/2312.02674)  
Mila Gorecki, Jakob H. Macke, Michael Deistler

- **Optimal simulation-based Bayesian decisions** [[arXiv]](https://arxiv.org/abs/2311.05742)  
Justin Alsing, Thomas D. P. Edwards, Benjamin Wandelt

- **Graph-informed simulation-based inference for models of active matter** [[arXiv]](https://arxiv.org/abs/2304.06806)  
Namid R. Stillman, Silke Henkes, Roberto Mayor, Gilles Louppe

- **Simulation-based inference of single-molecule force spectroscopy** [[arXiv]](https://arxiv.org/abs/2209.10392)  
Lars Dingeldein, Pilar Cossio, Roberto Covino

- **Normalizing flows for likelihood-free inference with fusion simulations** [[Paper]](https://iopscience.iop.org/article/10.1088/1361-6587/ac828d)  
C S Furia, R M Churchill

- **Amortized Bayesian Inference of GISAXS Data with Normalizing Flows** [[arXiv]](https://arxiv.org/abs/2210.01543)  
Maksim Zhdanov, Lisa Randolph, Thomas Kluge, Motoaki Nakatsutsumi, Christian Gutt, Marina Ganeva, Nico Hoffmann

- **Optimal Design of Experiments for Simulation-Based Inference of Mechanistic Acyclic Biological Networks** [[arXiv]](https://arxiv.org/abs/2111.13612)  
Vincent Zaballa, Elliot Hui

- **Simulation-based Bayesian inference for multi-fingered robotic grasping** [[arXiv]](https://arxiv.org/abs/2109.14275)  
Norman Marlier, Olivier Brüls, Gilles Louppe

- **Simulation-based inference of evolutionary parameters from adaptation dynamics using neural networks** [[bioRxiv]](https://www.biorxiv.org/content/10.1101/2021.09.30.462581v1.abstract)  
Grace Avecilla, Julie N. Chuong, Fangfei Li, Gavin Sherlock, David Gresham, Yoav Ram

## Application to Real Data
*Applications of neural simulation-based inference beyond synthetic data.*

- **A robust neural determination of the source-count distribution of the Fermi-LAT sky at high latitudes** [[arXiv]](https://arxiv.org/abs/2505.02906)  
Christopher Eckner, Noemi Anau Montel, Florian List, Francesca Calore, Christoph Weniger

- **SimBIG : A Forward Modeling Approach To Analyzing Galaxy Clustering** [[arXiv]](https://arxiv.org/abs/2211.00723)  
ChangHoon Hahn et al

- **A neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess** [[arXiv]](https://arxiv.org/abs/2110.06931)  
Siddharth Mishra-Sharma, Kyle Cranmer

- **Towards constraining warm dark matter with stellar streams through neural simulation-based inference** *(Preliminary)* [[arXiv]](https://arxiv.org/abs/2011.14923)  
Joeri Hermans, Nilanjan Banik, Christoph Weniger, Gianfranco Bertone, Gilles Louppe

- **Likelihood-free inference with neural compression of DES SV weak lensing map statistics** [[arXiv]](https://arxiv.org/abs/2009.08459)  
Niall Jeffrey, Justin Alsing, François Lanusse

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