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- **Normalizing flows for probabilistic modeling and inference** (2021)<br />by George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan<br />[[Paper]](https://arxiv.org/abs/1912.02762)
- **Normalizing flows for probabilistic modeling and inference** (2021)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan<br />[[Paper]](https://arxiv.org/abs/1912.02762)
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- **The frontier of simulation-based inference** (2020)<br />by Kyle Cranmer, Johann Brehmer, Gilles Louppe<br />[[Paper]](http://dx.doi.org/10.1073/pnas.1912789117)
- **The frontier of simulation-based inference** (2020)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Kyle Cranmer, Johann Brehmer, Gilles Louppe<br />[[Paper]](http://dx.doi.org/10.1073/pnas.1912789117)
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## Software

- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**<br />[[Code]](https://bayesflow.org/)
- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />[[Code]](https://bayesflow.org/)
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- **sbi: A toolkit for simulation-based inference**<br />[[Code]](https://sbi-dev.github.io/sbi/latest/)
- **sbi: A toolkit for simulation-based inference**<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />[[Code]](https://sbi-dev.github.io/sbi/latest/)
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## Methodological Papers

- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems** (2024)<br />by Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems** (2024)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
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- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference** (2023)<br />by Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf<br />[[Paper]](http://dx.doi.org/10.1103/PhysRevLett.130.171403)
- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference** (2023)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf<br />[[Paper]](http://dx.doi.org/10.1103/PhysRevLett.130.171403)
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- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models** (2023)<br />by Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner<br />[[Paper]](https://proceedings.mlr.press/v216/radev23a)
- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models** (2023)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner<br />[[Paper]](https://proceedings.mlr.press/v216/radev23a)
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## Application Papers

- **Evaluating Sparse Galaxy Simulations via Out-of-Distribution Detection and Amortized Bayesian Model Comparison** (2024)<br />by Lingyi Zhou, Stefan T. Radev, William H. Oliver, Aura Obreja, Zehao Jin, Tobias Buck<br />[[Paper]](https://arxiv.org/abs/2410.10606)
- **Evaluating Sparse Galaxy Simulations via Out-of-Distribution Detection and Amortized Bayesian Model Comparison** (2024)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Lingyi Zhou, Stefan T. Radev, William H. Oliver, Aura Obreja, Zehao Jin, Tobias Buck<br />[[Paper]](https://arxiv.org/abs/2410.10606)
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## Uncategorized

- **Flow Matching for Scalable Simulation-Based Inference** (2023)<br />by Jonas Bernhard Wildberger, Maximilian Dax, Simon Buchholz, Stephen R Green, Jakob H. Macke, Bernhard Schölkopf<br />[[Paper]](https://openreview.net/forum?id=D2cS6SoYlP) [[Code]](https://github.com/dingo-gw/flow-matching-posterior-estimation)
- **Flow Matching for Scalable Simulation-Based Inference** (2023)<br />_TLDR: Reading this paper? Please consider contributing a TLDR summary._<br />by Jonas Bernhard Wildberger, Maximilian Dax, Simon Buchholz, Stephen R Green, Jakob H. Macke, Bernhard Schölkopf<br />[[Paper]](https://openreview.net/forum?id=D2cS6SoYlP) [[Code]](https://github.com/dingo-gw/flow-matching-posterior-estimation)
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