Update README.md [GH Action]

README.md

@@ -1,12 +1,10 @@
-# Awesome Amortized Inference
 
+# Awesome Amortized Inference
 
 [![Awesome](https://awesome.re/badge-flat2.svg)](https://awesome.re)
 ![Contributions Welcome](https://img.shields.io/badge/Contributions-Welcome-brightgreen)
 ![License: CC0](https://img.shields.io/badge/License-CC0_1.0-lightgrey)
 
-
-
 Welcome to the Awesome Amortized Inference repository!
 This is a curated list of resources, including overviews, software, papers, and other resources related to amortized inference.
 Feel free to explore the entries below and use the provided BibTeX information for citation purposes.
@@ -27,7 +25,30 @@ We highly recommend checking out the `awesome-neural-sbi` list for more resource
 > that are specifically designated to *simulation-based inference* and not *amortized inference* (which doesn't need to be simulation-based).
 > Once we figure out the direction and deem the project potentially useful for the community, we'll launch and add an extensive set of resources 
 > -- hopefully with the help of many awesome people from the community 🧡
-## Overview
+
+
+## Contents
+
+- [Overview Articles](#overview)
+- [Software](#software)
+- [Research Articles](#paper)
+- [Uncategorized](#uncategorized)
+
+
+## Overview Articles
+
+- **Neural Methods for Amortized Inference** (2024)<br />_TLDR: Overview paper of amortized point estimators and full posterior estimators._<br />by Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser<br />[[Paper]](https://arxiv.org/abs/2404.12484) 
+  <details>
+  <summary>Show BibTeX</summary>
+  <pre><code>
+  @misc{zammit-mangion2024neural,
+  title = {Neural Methods for Amortized Inference},
+  publisher = {arXiv},
+  year = {2024},
+  author = {Zammit-Mangion, Andrew and Sainsbury-Dale, Matthew and Huser, Raphaël}
+  }
+  </code>
+  </pre></details>
 
 - **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) 
   <details>
@@ -49,19 +70,6 @@ We highly recommend checking out the `awesome-neural-sbi` list for more resource
   </code>
   </pre></details>
 
-- **Neural Methods for Amortized Inference** (2024)<br />_TLDR: Overview paper of amortized point estimators and full posterior estimators._<br />by Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser<br />[[Paper]](https://arxiv.org/abs/2404.12484) 
-  <details>
-  <summary>Show BibTeX</summary>
-  <pre><code>
-  @misc{zammit-mangion2024neural,
-  title = {Neural Methods for Amortized Inference},
-  publisher = {arXiv},
-  year = {2024},
-  author = {Zammit-Mangion, Andrew and Sainsbury-Dale, Matthew and Huser, Raphaël}
-  }
-  </code>
-  </pre></details>
-
 - **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) 
   <details>
   <summary>Show BibTeX</summary>
@@ -117,7 +125,34 @@ We highly recommend checking out the `awesome-neural-sbi` list for more resource
   }
   </code>
   </pre></details>
-## Paper
+## Research Articles
+
+- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems** (2024)<br />by Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
+  <details>
+  <summary>Show BibTeX</summary>
+  <pre><code>
+  @misc{orozco2024aspire,
+  Title = {ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems},
+  Year = {2024},
+  Eprint = {arXiv:2405.05398},
+  author = {Orozco, Rafael and Siahkoohi, Ali and Louboutin, Mathias and Herrmann, Felix J.}
+  }
+  </code>
+  </pre></details>
+
+- **Sensitivity-Aware Amortized Bayesian Inference** (2024)<br />_TLDR: Efficient amortized sensitivity analyses with context variables_<br />by Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Koethe, Stefan T. Radev<br />[[Code]](https://github.com/bayesflow-org/SA-ABI) [[Paper]](https://openreview.net/forum?id=Kxtpa9rvM0) 
+  <details>
+  <summary>Show BibTeX</summary>
+  <pre><code>
+  @article{elsemueller2024sensitivity,
+  title = {Sensitivity-Aware Amortized Bayesian Inference},
+  journal = {Transactions on Machine Learning Research},
+  issn = {2835-8856},
+  year = {2024},
+  author = {Elsem{\"u}ller, Lasse and Olischl{\"a}ger, Hans and Schmitt, Marvin and B{\"u}rkner, Paul-Christian and Koethe, Ullrich and Radev, Stefan T.}
+  }
+  </code>
+  </pre></details>
 
 - **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) 
   <details>
@@ -153,33 +188,6 @@ We highly recommend checking out the `awesome-neural-sbi` list for more resource
   }
   </code>
   </pre></details>
-
-- **ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems** (2024)<br />by Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
-  <details>
-  <summary>Show BibTeX</summary>
-  <pre><code>
-  @misc{orozco2024aspire,
-  Title = {ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems},
-  Year = {2024},
-  Eprint = {arXiv:2405.05398},
-  author = {Orozco, Rafael and Siahkoohi, Ali and Louboutin, Mathias and Herrmann, Felix J.}
-  }
-  </code>
-  </pre></details>
-
-- **Sensitivity-Aware Amortized Bayesian Inference** (2024)<br />_TLDR: Efficient amortized sensitivity analyses with context variables_<br />by Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Koethe, Stefan T. Radev<br />[[Code]](https://github.com/bayesflow-org/SA-ABI) [[Paper]](https://openreview.net/forum?id=Kxtpa9rvM0) 
-  <details>
-  <summary>Show BibTeX</summary>
-  <pre><code>
-  @article{elsemueller2024sensitivity,
-  title = {Sensitivity-Aware Amortized Bayesian Inference},
-  journal = {Transactions on Machine Learning Research},
-  issn = {2835-8856},
-  year = {2024},
-  author = {Elsem{\"u}ller, Lasse and Olischl{\"a}ger, Hans and Schmitt, Marvin and B{\"u}rkner, Paul-Christian and Koethe, Ullrich and Radev, Stefan T.}
-  }
-  </code>
-  </pre></details>
 ## 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)