---
title: "Who cites Contemporary Symbolic — 19 citing papers"
description: "19 papers of the Elamur Research library cite «Contemporary Symbolic Regression Methods and their Relative Performance», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/cava-2021-contemporary-symbolic-regression-methods/cited-by/"
---
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# Who cites «Contemporary Symbolic Regression Methods and their Relative Performance»

19 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Contemporary Symbolic Regression Methods and their Relative Performance»](https://md.research.elamur.ai/free/en/papers/cava-2021-contemporary-symbolic-regression-methods/)

1. [**Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl arXiv:2305.01582**Miles Cranmer (Princeton University, Flatiron Institute)*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/university-2023-interpretable-machine-learning-science/)
2. [**LLM-SR: Scientific Equation Discovery via Programming with Large Language Models arXiv:2404.18400**Parshin Shojaee, Kazem Meidani, Shashank Gupta, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/shojaee-2024-llm-sr-scientific-equation/)
3. [**Symbolic Regression is NP-hard arXiv:2207.01018**Marco Virgolin, Solon P. Pissis*2022 · 35 citations*](https://md.research.elamur.ai/free/en/papers/virgolin-2022-symbolic-regression-np-hard/)
4. [**LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery arXiv:2405.09783**Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ma-2024-llm-simulation-bilevel-optimizers-new/)
5. [**End-to-end symbolic regression with transformers arXiv:2204.10532**Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, et al.*2022 · 27 citations*](https://md.research.elamur.ai/free/en/papers/kamienny-2022-end-end-symbolic-regression-transformers/)
6. **[Symbolic Regression with a Learned Concept Library](https://md.research.elamur.ai/free/en/papers/grayeli-2024-symbolic-regression-learned-concept-library/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.*2024 · 23 citations*
7. [**SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training arXiv:2310.02227**Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, et al.*2023 · 8 citations*](https://md.research.elamur.ai/free/en/papers/meidani-2023-snip-bridging-mathematical-symbolic-numeric/)

12 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/cava-2021-contemporary-symbolic-regression-methods/) — Contemporary Symbolic Regression Methods and their Relative Performance