🔗 Who cites «Discovering Symbolic Models from Deep Learning with Inductive Biases»

22 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 «Discovering Symbolic Models from Deep Learning with Inductive Biases»

1. Interpretable Machine Learning for Science with PySR and SymbolicRegression.jlarXiv:2305.01582Miles Cranmer (Princeton University, Flatiron Institute)2023 · 216 citations
2. End-to-end symbolic regression with transformersarXiv:2204.10532Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, et al.2022 · 27 citations
3. 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
4. Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery SystemsMachine LearningStefan Kramer, Mattia Cerrato, Jannis Brugger, et al.2023 · 13 citations
5. Neuro-Symbolic Artificial Intelligence: Current TrendsarXiv:2105.05330Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, et al.2021 · 12 citations
6. SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-trainingarXiv:2310.02227Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, et al.2023 · 8 citations
7. Neurosymbolic Programming for SciencearXiv:2210.05050Jennifer J. Sun, Megan Tjandrasuwita, Atharva Sehgal, et al.2022 · 6 citations

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

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