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README.md

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@@ -18,18 +18,7 @@ Contributions are always welcome, this is a community-driven project.
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{papamakarios2021normalizing,
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&nbsp;&nbsp;title = {Normalizing flows for probabilistic modeling and inference},
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&nbsp;&nbsp;year = {2021},
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&nbsp;&nbsp;publisher = {JMLR.org},
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&nbsp;&nbsp;volume = {22},
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&nbsp;&nbsp;number = {1},
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&nbsp;&nbsp;issn = {1532-4435},
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&nbsp;&nbsp;journal = {J. Mach. Learn. Res.},
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&nbsp;&nbsp;month = {jan},
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&nbsp;&nbsp;articleno = {57},
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&nbsp;&nbsp;numpages = {64},
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&nbsp;&nbsp;category = {overview},
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&nbsp;&nbsp;author = {Papamakarios, George and Nalisnick, Eric and Rezende, Danilo Jimenez and Mohamed, Shakir and Lakshminarayanan, Balaji}
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title = {Normalizing flows for probabilistic modeling and inference}, year = {2021}, publisher = {JMLR.org}, volume = {22}, number = {1}, issn = {1532-4435}, journal = {J. Mach. Learn. Res.}, month = {jan}, articleno = {57}, numpages = {64}, category = {overview}, author = {Papamakarios, George and Nalisnick, Eric and Rezende, Danilo Jimenez and Mohamed, Shakir and Lakshminarayanan, Balaji}
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}
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</code>
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</pre></details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@misc{zammit-mangion2024neural,
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&nbsp;&nbsp;title = {Neural Methods for Amortized Inference},
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&nbsp;&nbsp;publisher = {arXiv},
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&nbsp;&nbsp;year = {2024},
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&nbsp;&nbsp;category = {overview},
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&nbsp;&nbsp;author = {Zammit-Mangion, Andrew and Sainsbury-Dale, Matthew and Huser, Raphaël}
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title = {Neural Methods for Amortized Inference}, publisher = {arXiv}, year = {2024}, category = {overview}, author = {Zammit-Mangion, Andrew and Sainsbury-Dale, Matthew and Huser, Raphaël}
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}
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</code>
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</pre></details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{Cranmer2020,
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&nbsp;&nbsp;title = {The frontier of simulation-based inference},
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&nbsp;&nbsp;volume = {117},
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&nbsp;&nbsp;ISSN = {1091-6490},
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&nbsp;&nbsp;DOI = {10.1073/pnas.1912789117},
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&nbsp;&nbsp;number = {48},
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&nbsp;&nbsp;journal = {Proceedings of the National Academy of Sciences},
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&nbsp;&nbsp;publisher = {Proceedings of the National Academy of Sciences},
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&nbsp;&nbsp;year = {2020},
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&nbsp;&nbsp;pages = {30055–30062},
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&nbsp;&nbsp;category = {overview},
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&nbsp;&nbsp;author = {Cranmer, Kyle and Brehmer, Johann and Louppe, Gilles}
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title = {The frontier of simulation-based inference}, volume = {117}, ISSN = {1091-6490}, DOI = {10.1073/pnas.1912789117}, number = {48}, journal = {Proceedings of the National Academy of Sciences}, publisher = {Proceedings of the National Academy of Sciences}, year = {2020}, pages = {30055–30062}, category = {overview}, author = {Cranmer, Kyle and Brehmer, Johann and Louppe, Gilles}
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}
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</code>
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</pre></details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{radev2023bayesflow,
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&nbsp;&nbsp;doi = {10.21105/joss.05702},
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&nbsp;&nbsp;year = {2023},
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&nbsp;&nbsp;publisher = {The Open Journal},
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&nbsp;&nbsp;volume = {8},
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&nbsp;&nbsp;number = {89},
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&nbsp;&nbsp;pages = {5702},
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&nbsp;&nbsp;title = {BayesFlow: Amortized Bayesian Workflows With Neural Networks},
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&nbsp;&nbsp;journal = {Journal of Open Source Software},
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&nbsp;&nbsp;category = {software},
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&nbsp;&nbsp;author = {Radev, Stefan T. and Schmitt, Marvin and Schumacher, Lukas and Elsemüller, Lasse and Pratz, Valentin and Schälte, Yannik and Köthe, Ullrich and Bürkner, Paul-Christian}
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doi = {10.21105/joss.05702}, year = {2023}, publisher = {The Open Journal}, volume = {8}, number = {89}, pages = {5702}, title = {BayesFlow: Amortized Bayesian Workflows With Neural Networks}, journal = {Journal of Open Source Software}, category = {software}, author = {Radev, Stefan T. and Schmitt, Marvin and Schumacher, Lukas and Elsemüller, Lasse and Pratz, Valentin and Schälte, Yannik and Köthe, Ullrich and Bürkner, Paul-Christian}
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}
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</code>
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</pre></details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{tejero-cantero2020sbi,
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&nbsp;&nbsp;doi = {10.21105/joss.02505},
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&nbsp;&nbsp;year = {2020},
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&nbsp;&nbsp;publisher = {The Open Journal},
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&nbsp;&nbsp;volume = {5},
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&nbsp;&nbsp;number = {52},
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&nbsp;&nbsp;pages = {2505},
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&nbsp;&nbsp;title = {sbi: A toolkit for simulation-based inference},
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&nbsp;&nbsp;journal = {Journal of Open Source Software},
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&nbsp;&nbsp;category = {software},
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&nbsp;&nbsp;author = {Tejero-Cantero, Alvaro and Boelts, Jan and Deistler, Michael and Lueckmann, Jan-Matthis and Durkan, Conor and Gonçalves, Pedro J. and Greenberg, David S. and Macke, Jakob H.}
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doi = {10.21105/joss.02505}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {52}, pages = {2505}, title = {sbi: A toolkit for simulation-based inference}, journal = {Journal of Open Source Software}, category = {software}, author = {Tejero-Cantero, Alvaro and Boelts, Jan and Deistler, Michael and Lueckmann, Jan-Matthis and Durkan, Conor and Gonçalves, Pedro J. and Greenberg, David S. and Macke, Jakob H.}
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}
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</code>
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</pre></details>
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<pre><code>
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@article{dax2023neural,
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&nbsp;&nbsp;title = {Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference},
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&nbsp;&nbsp;volume = {130},
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&nbsp;&nbsp;ISSN = {1079-7114},
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&nbsp;&nbsp;DOI = {10.1103/physrevlett.130.171403},
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&nbsp;&nbsp;number = {17},
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&nbsp;&nbsp;journal = {Physical Review Letters},
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&nbsp;&nbsp;publisher = {American Physical Society (APS)},
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&nbsp;&nbsp;year = {2023},
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&nbsp;&nbsp;category = {paper},
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&nbsp;&nbsp;author = {Dax, Maximilian and Green, Stephen R. and Gair, Jonathan and P\"{u}rrer, Michael and Wildberger, Jonas and Macke, Jakob H. and Buonanno, Alessandra and Sch\"{o}lkopf, Bernhard}
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title = {Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference}, volume = {130}, ISSN = {1079-7114}, DOI = {10.1103/physrevlett.130.171403}, number = {17}, journal = {Physical Review Letters}, publisher = {American Physical Society (APS)}, year = {2023}, category = {paper}, author = {Dax, Maximilian and Green, Stephen R. and Gair, Jonathan and P\"{u}rrer, Michael and Wildberger, Jonas and Macke, Jakob H. and Buonanno, Alessandra and Sch\"{o}lkopf, Bernhard}
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}
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</code>
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</pre></details>
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<pre><code>
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@inproceedings{radev2023jana,
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&nbsp;&nbsp;title = {{JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models}},
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&nbsp;&nbsp;booktitle = {Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence},
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&nbsp;&nbsp;pages = {1695--1706},
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&nbsp;&nbsp;year = {2023},
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&nbsp;&nbsp;volume = {216},
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&nbsp;&nbsp;series = {Proceedings of Machine Learning Research},
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&nbsp;&nbsp;publisher = {PMLR},
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&nbsp;&nbsp;category = {paper},
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&nbsp;&nbsp;author = {Radev, Stefan T. and Schmitt, Marvin and Pratz, Valentin and Picchini, Umberto and K\"othe, Ullrich and B\"urkner, Paul-Christian}
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title = {{JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models}}, booktitle = {Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence}, pages = {1695--1706}, year = {2023}, volume = {216}, series = {Proceedings of Machine Learning Research}, publisher = {PMLR}, category = {paper}, author = {Radev, Stefan T. and Schmitt, Marvin and Pratz, Valentin and Picchini, Umberto and K\"othe, Ullrich and B\"urkner, Paul-Christian}
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}
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</code>
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</pre></details>
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<pre><code>
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@misc{orozco2024aspire,
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&nbsp;&nbsp;Title = {ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems},
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&nbsp;&nbsp;Year = {2024},
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&nbsp;&nbsp;Eprint = {arXiv:2405.05398},
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&nbsp;&nbsp;category = {paper},
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&nbsp;&nbsp;author = {Orozco, Rafael and Siahkoohi, Ali and Louboutin, Mathias and Herrmann, Felix J.}
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Title = {ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems}, Year = {2024}, Eprint = {arXiv:2405.05398}, category = {paper}, author = {Orozco, Rafael and Siahkoohi, Ali and Louboutin, Mathias and Herrmann, Felix J.}
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}
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</code>
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</pre></details>

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