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‎README.md‎

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@@ -8,12 +8,8 @@ Contributioons always welcome, this shall be a community-driven project.
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Contribution guide will follow ASAP.
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## Overview
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- **Normalizing flows for probabilistic modeling and inference**
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Papamakarios, George, Nalisnick, Eric, Rezende, Danilo Jimenez, Mohamed, Shakir, Lakshminarayanan, Balaji
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<details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{papamakarios2021normalizing,
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- **Normalizing flows for probabilistic modeling and inference**. Papamakarios, George, Nalisnick, Eric, Rezende, Danilo Jimenez, Mohamed, Shakir, Lakshminarayanan, Balaji. <details> <summary>Show BibTeX</summary>
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<pre><code>@article{papamakarios2021normalizing,
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category = {overview},
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numpages = {64},
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articleno = {57},
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year = {2021},
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title = {Normalizing flows for probabilistic modeling and inference},
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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></pre>
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</details>
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}</code></pre>
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</details>
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## Software
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- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**
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Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
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[Link](https://bayesflow.org/)
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<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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- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**. Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner. [[Link]](https://bayesflow.org/) <details> <summary>Show BibTeX</summary>
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<pre><code>@article{radev2023bayesflow,
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category = {software},
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journal = {Journal of Open Source Software},
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title = {BayesFlow: Amortized Bayesian Workflows With Neural Networks},
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year = {2023},
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url = {https://bayesflow.org/},
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doi = {10.21105/joss.05702}
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}
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</code></pre>
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</details>
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- **sbi: A toolkit for simulation-based inference**
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Alvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann, Conor Durkan, Pedro J. Gonçalves, David S. Greenberg, Jakob H. Macke
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[Link](https://sbi-dev.github.io/sbi/latest/)
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<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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}</code></pre>
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</details>
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- **sbi: A toolkit for simulation-based inference**. Alvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann, Conor Durkan, Pedro J. Gonçalves, David S. Greenberg, Jakob H. Macke. [[Link]](https://sbi-dev.github.io/sbi/latest/) <details> <summary>Show BibTeX</summary>
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<pre><code>@article{tejero-cantero2020sbi,
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category = {software},
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journal = {Journal of Open Source Software},
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title = {sbi: A toolkit for simulation-based inference},
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year = {2020},
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url = {https://sbi-dev.github.io/sbi/latest/},
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doi = {10.21105/joss.02505}
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}
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</code></pre>
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</details>
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}</code></pre>
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</details>
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## Paper
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- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference**
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Dax, Maximilian, Green, Stephen R., Gair, Jonathan, P\"{u}rrer, Michael, Wildberger, Jonas, Macke, Jakob H., Buonanno, Alessandra, Sch\"{o}lkopf, Bernhard
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[Link](http://dx.doi.org/10.1103/PhysRevLett.130.171403)
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<details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@article{dax2023neural,
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- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference**. Dax, Maximilian, Green, Stephen R., Gair, Jonathan, P\"{u}rrer, Michael, Wildberger, Jonas, Macke, Jakob H., Buonanno, Alessandra, Sch\"{o}lkopf, Bernhard. [[Link]](http://dx.doi.org/10.1103/PhysRevLett.130.171403) <details> <summary>Show BibTeX</summary>
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<pre><code>@article{dax2023neural,
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category = {paper},
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year = {2023},
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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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issn = {1079-7114},
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volume = {130},
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title = {Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference}
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}
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</code></pre>
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</details>
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}</code></pre>
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</details>
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- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models**
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Radev, Stefan T., Schmitt, Marvin, Pratz, Valentin, Picchini, Umberto, K\"othe, Ullrich, B\"urkner, Paul-Christian
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<details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@inproceedings{radev2023jana,
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- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models**. Radev, Stefan T., Schmitt, Marvin, Pratz, Valentin, Picchini, Umberto, K\"othe, Ullrich, B\"urkner, Paul-Christian. <details> <summary>Show BibTeX</summary>
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<pre><code>@inproceedings{radev2023jana,
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category = {paper},
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publisher = {PMLR},
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series = {Proceedings of Machine Learning Research},
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booktitle = {Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence},
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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}}
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}
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</code></pre>
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</details>
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- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems**
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Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
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[Link](https://arxiv.org/abs/2405.05398)
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<details>
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<summary>Show BibTeX</summary>
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<pre><code>
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@misc{orozco2024aspire,
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}</code></pre>
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</details>
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- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems**. Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann. [[Link]](https://arxiv.org/abs/2405.05398) <details> <summary>Show BibTeX</summary>
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<pre><code>@misc{orozco2024aspire,
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category = {paper},
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url = {https://arxiv.org/abs/2405.05398},
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eprint = {arXiv:2405.05398},
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year = {2024},
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title = {ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems},
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author = {Rafael Orozco and Ali Siahkoohi and Mathias Louboutin and Felix J. Herrmann}
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}
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</code></pre>
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</details>
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}</code></pre>
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</details>
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