--- title: "Who cites AI Feynman: a Physics-Inspired — 34 citing papers" description: "34 papers of the Elamur Research library cite «AI Feynman: a Physics-Inspired Method for Symbolic Regression», found in their…" canonical: "https://research.elamur.ai/free/en/papers/udrescu-2019-ai-feynman-physics-inspired/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/udrescu-2019-ai-feynman-physics-inspired/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [AI Feynman: a Physics-Inspired Method for…](https://md.research.elamur.ai/free/en/papers/udrescu-2019-ai-feynman-physics-inspired/) / cited by # Who cites «AI Feynman: a Physics-Inspired Method for Symbolic Regression» 34 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «AI Feynman: a Physics-Inspired Method for Symbolic Regression»](https://md.research.elamur.ai/free/en/papers/udrescu-2019-ai-feynman-physics-inspired/) 1. [**Discovering Symbolic Models from Deep Learning with Inductive Biases arXiv:2006.11287**Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, et al.*2020 · 272 citations*](https://md.research.elamur.ai/free/en/papers/cranmer-2020-discovering-symbolic-models-deep/) 2. [**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/) 3. [**Contemporary Symbolic Regression Methods and their Relative Performance arXiv:2107.14351**William La Cava, Patryk Orzechowski, Bogdan Burlacu, et al.*2021 · 156 citations*](https://md.research.elamur.ai/free/en/papers/cava-2021-contemporary-symbolic-regression-methods/) 4. [**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/) 5. **[From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery](https://md.research.elamur.ai/free/en/papers/zheng-2025-automation-autonomy-survey-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.*2025 · 39 citations* 6. [**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/) 7. [**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/) 8. **[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* 9. [**LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models arXiv:2504.10415**Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/shojaee-2025-llm-srbench-new-benchmark/) 10. **[Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems](https://md.research.elamur.ai/free/en/papers/kramer-2023-automated-scientific-discovery-equation/) [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)**Stefan Kramer, Mattia Cerrato, Jannis Brugger, et al.*2023 · 13 citations* 11. [**DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and Experience arXiv:2506.04282**Runxiang Wang, Boxiao Wang, Kai Li, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-drsr-llm-based-scientific-equation/) 12. [**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/) 13. [**A Survey of AI Scientists arXiv:2510.23045**Guiyao Tie, Pan Zhou, Lichao Sun*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/tie-2025-survey-ai-scientists/) 14. [**The Past and Future of AI Scientists arXiv:2608.14407**Ross D. King*2026*](https://md.research.elamur.ai/free/en/papers/king-2026-past-future-ai-scientists/) 20 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/udrescu-2019-ai-feynman-physics-inspired/) — AI Feynman: a Physics-Inspired Method for Symbolic Regression