PySR / CITATION.md
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# Citing
To cite PySR or SymbolicRegression.jl, please use the following BibTeX entry:
```bibtex
@misc{cranmerInterpretableMachineLearning2023,
title = {Interpretable {Machine} {Learning} for {Science} with {PySR} and {SymbolicRegression}.jl},
url = {http://arxiv.org/abs/2305.01582},
doi = {10.48550/arXiv.2305.01582},
urldate = {2023-07-17},
publisher = {arXiv},
author = {Cranmer, Miles},
month = may,
year = {2023},
note = {arXiv:2305.01582 [astro-ph, physics:physics]},
keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Computer Science - Symbolic Computation, Physics - Data Analysis, Statistics and Probability},
}
```
To cite symbolic distillation of neural networks, the following BibTeX entry can be used:
```bibtex
@article{cranmerDiscovering2020,
title={Discovering Symbolic Models from Deep Learning with Inductive Biases},
author={Miles Cranmer and Alvaro Sanchez-Gonzalez and Peter Battaglia and Rui Xu and Kyle Cranmer and David Spergel and Shirley Ho},
journal={NeurIPS 2020},
year={2020},
eprint={2006.11287},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```