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README.md

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# Awesome Amortized Inference
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Welcome to the Awesome Amortized Inference repository!
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This is a curated list of resources, including overviews, software, papers, and other resources related to amortized inference.
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Feel free to explore the entries below and use the provided BibTeX information for citation purposes.
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Contributions are always welcome, this is a community-driven project.
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## Overview
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- **Normalizing flows for probabilistic modeling and inference**.<br /> George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
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- **Normalizing flows for probabilistic modeling and inference**.<br /> George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan
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<details>
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<summary>Show BibTeX</summary>
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- **Neural Methods for Amortized Inference**. [[Paper]](https://arxiv.org/abs/2404.12484) <br /> Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser
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- **Neural Methods for Amortized Inference**. [[Paper]](https://arxiv.org/abs/2404.12484) <br /> Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser
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<summary>Show BibTeX</summary>
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</pre></details>
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- **The frontier of simulation-based inference**. [[Paper]](http://dx.doi.org/10.1073/pnas.1912789117) <br /> Kyle Cranmer, Johann Brehmer, Gilles Louppe
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- **The frontier of simulation-based inference**. [[Paper]](http://dx.doi.org/10.1073/pnas.1912789117) <br /> Kyle Cranmer, Johann Brehmer, Gilles Louppe
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<summary>Show BibTeX</summary>
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}
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## Software
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- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**. [[Code]](https://bayesflow.org/) <br /> Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
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- **BayesFlow: Amortized Bayesian Workflows With Neural Networks**. [[Code]](https://bayesflow.org/) <br /> Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
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<details>
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<summary>Show BibTeX</summary>
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- **sbi: A toolkit for simulation-based inference**. [[Code]](https://sbi-dev.github.io/sbi/latest/) <br /> 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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- **sbi: A toolkit for simulation-based inference**. [[Code]](https://sbi-dev.github.io/sbi/latest/) <br /> 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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<summary>Show BibTeX</summary>
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## Paper
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- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference**. [[Paper]](http://dx.doi.org/10.1103/PhysRevLett.130.171403) <br /> Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
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- **Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference**. [[Paper]](http://dx.doi.org/10.1103/PhysRevLett.130.171403) <br /> Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
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- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models**. [[Paper]](https://proceedings.mlr.press/v216/radev23a) <br /> Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
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- **JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models**. [[Paper]](https://proceedings.mlr.press/v216/radev23a) <br /> Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
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- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems**. [[Paper]](https://arxiv.org/abs/2405.05398) <br /> Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
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- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems**. [[Paper]](https://arxiv.org/abs/2405.05398) <br /> Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
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<pre><code>

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