Add paper (#31)

* Add citation in README

* Add citation to docs landing page

* Add cite and star hint

* Add paper and project page

* Change heading levels

* Change heading levels in docs landing page

* Change wording

README.md

@@ -19,17 +19,20 @@
 </p>
 
 <p align="center">
-<a href="https://github.com/tum-pbs/apebench-paper">
-    📝 Paper Project Page
-</a>
+    <a href="https://arxiv.org/abs/2411.00180">
+        📄 Paper
+    </a> •
+    <a href="https://tum-pbs.github.io/apebench-paper/">
+        🧵 Project Page
+    </a>
 </p>
 
 <p align="center">
   <a href="#installation">Installation</a> •
   <a href="#quickstart">Quickstart</a> •
     <a href="#documentation">Documentation</a> •
     <a href="#background">Background</a> •
-    <a href="#acknowledgements">Acknowledgements</a>
+    <a href="#citation">Citation</a>
 </p>
 
 <p align="center">
@@ -184,17 +187,30 @@ APEBench encapsulates the entire pipeline of training and evaluating an
 autoregressive neural emulator in a scenario. A scenario is a callable
 dataclass.
 
-## Acknowledgements
-
-### Citation
+## Citation
+
+This package was developed as part of the [APEBench paper
+(arxiv.org/abs/2411.00180)](https://arxiv.org/abs/2411.00180) (accepted at
+Neurips 2024). If you find it useful for your research, please consider citing
+it:
+
+```bibtex
+@article{koehler2024apebench,
+  title={{APEBench}: A Benchmark for Autoregressive Neural Emulators of {PDE}s},
+  author={Felix Koehler and Simon Niedermayr and R{\"}udiger Westermann and Nils Thuerey},
+  journal={Advances in Neural Information Processing Systems (NeurIPS)},
+  volume={38},
+  year={2024}
+}
+```
 
-This package was developed as part of the `APEBench paper` (accepted at Neurips 2024), we will soon add the citation here.
+(Feel free to also give the project a star on GitHub if you like it.)
 
-### Funding
+## Funding
 
 The main author (Felix Koehler) is a PhD student in the group of [Prof. Thuerey at TUM](https://ge.in.tum.de/) and his research is funded by the [Munich Center for Machine Learning](https://mcml.ai/).
 
-### License
+## License
 
 MIT, see [here](https://github.com/Ceyron/apebench/blob/main/LICENSE.txt)
 

docs/index.md

@@ -122,17 +122,30 @@ APEBench encapsulates the entire pipeline of training and evaluating an
 autoregressive neural emulator in a scenario. A scenario is a callable
 dataclass.
 
-## Acknowledgements
-
-### Citation
+## Citation
+
+This package was developed as part of the [APEBench paper
+(arxiv.org/abs/2411.00180)](https://arxiv.org/abs/2411.00180) (accepted at
+Neurips 2024). If you find it useful for your research, please consider citing
+it:
+
+```bibtex
+@article{koehler2024apebench,
+  title={{APEBench}: A Benchmark for Autoregressive Neural Emulators of {PDE}s},
+  author={Felix Koehler and Simon Niedermayr and R{\"}udiger Westermann and Nils Thuerey},
+  journal={Advances in Neural Information Processing Systems (NeurIPS)},
+  volume={38},
+  year={2024}
+}
+```
 
-This package was developed as part of the `APEBench paper` (accepted at Neurips 2024), we will soon add the citation here.
+(Feel free to also give the project a star on GitHub if you like it.)
 
-### Funding
+## Funding
 
 The main author (Felix Koehler) is a PhD student in the group of [Prof. Thuerey at TUM](https://ge.in.tum.de/) and his research is funded by the [Munich Center for Machine Learning](https://mcml.ai/).
 
-### License
+## License
 
 MIT, see [here](https://github.com/Ceyron/apebench/blob/main/LICENSE.txt)