Citation notice #5021 · 2026-07-11 03:19:08.722131+00:00
ERBench: A Benchmark and Testsuite for Equation Discovery Algorithms
Correction
Crossref
Open
cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, which carries a correction notice dated 2020-03-04. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.
Citing paper Event page Original DOI Notice DOI File a formal challenge All reference changes
01Evidence
Raw extraction · bibliography line · bibliography index 4
doi: 10.1038/s41592-019-0686-2. [Online; accessed 24-April-2025]. Ekaterina (Katya) Vladislavleva, Guido Smits, and Dick den Hertog. Order of nonlinearity as a complexity measure for models generated by symbolic regression via pareto genetic programming.Evolutionary Computation, IEEE Transactions on, 13:333 – 349, 05 2009. doi: 10.1109/TEVC.2008.926486. Wikipedia. List of scientific equations named after people — Wikipedia, the free en- cyclopedia. http://en.wikipedia.org/w/index.php?title=List%20of%20scientific% 20equations%20named%20after%20people&oldid=1249228356, 2025. [Online; accessed 24-April-2025]. Piotr Wyrwiński and Krzysztof Krawiec. Guiding genetic programming with graph neural networks. InProceedings of the Genetic and Evolutionary Computation Conference Com- panion, GECCO ’24 Companion, page 551–554, New York, NY, USA, 2024. Association for Computing Machinery. ISBN 9798400704956. doi: 10.1145/3638530.3654277. URL https://doi.org/10.1145/3638530.3654277. Yilong Xu, Yang Liu, and Hao Sun. Reinforcement symbolic regression machine. In The Twelfth International Conference on Learning Representations, 2024. URLhttps: //openreview.net/forum?id=PJVUWpPnZC. Kaizhong Zhang an
02Event
- Type
- Correction
- Source
- Crossref
- Original DOI
- 10.1038/s41592-019-0686-2
- Notice DOI
- 10.1038/s41592-020-0772-5
- Date
- 2020-03-04
- Title
- Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python
- Reasons
- ['Correction']
- Work
- SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python (2020) Nature Methods
03Dispute this notice
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