🔗 Who cites «Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl»

26 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 «Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl»

1. Large Language Models Are Zero-Shot Time Series ForecastersConference on Neural Information Processing Systems (NeurIPS)Nate Gruver, Marc Finzi, Shikai Qiu, et al.2023 · 268 citations
2. AlphaEvolve: A coding agent for scientific and algorithmic discoveryarXiv:2506.13131Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.2025 · 202 citations
3. LLM-SR: Scientific Equation Discovery via Programming with Large Language ModelsarXiv:2404.18400Parshin Shojaee, Kazem Meidani, Shashank Gupta, et al.2024 · 47 citations
4. Symbolic Regression with a Learned Concept LibraryConference on Neural Information Processing Systems (NeurIPS)Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.2024 · 23 citations
5. Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery SystemsMachine LearningStefan Kramer, Mattia Cerrato, Jannis Brugger, et al.2023 · 13 citations
6. DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and ExperiencearXiv:2506.04282Runxiang Wang, Boxiao Wang, Kai Li, et al.2025 · 9 citations
7. SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-trainingarXiv:2310.02227Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, et al.2023 · 8 citations

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

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