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Exhaustive Symbolic Regression

Published:2023 Issue: Volume: Page:1-1
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Bartlett Deaglan J.¹^ORCID,Desmond Harry²,Ferreira Pedro G.³

Affiliation:

1. CNRS and Sorbonne Université, Institut d’Astrophysique de Paris (IAP), UMR 7095, 98 bis bd Arago, Paris, France

2. Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Portsmouth, UK

3. Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, UK

Funder

Science and Technology Facilities Council

Beecroft Trust

European Research Council

Simons Foundation

Oriel College, University of Oxford

Royal Society

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/4358751/10136815.pdf?arnumber=10136815

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Class Symbolic Regression: Gotta Fit ’Em All;The Astrophysical Journal Letters;2024-07-01

2. SYREN-HALOFIT: A fast, interpretable, high-precision formula for the ΛCDM nonlinear matter power spectrum;Astronomy & Astrophysics;2024-06

3. A precise symbolic emulator of the linear matter power spectrum;Astronomy & Astrophysics;2024-06

4. Optimal inflationary potentials;Physical Review D;2024-04-18

5. Machine learning unveils the linear matter power spectrum of modified gravity;Physical Review D;2024-03-07

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