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Title:Discovery of exact equations for integer sequences
Authors:ID Gec, Boštjan, Institut "Jožef Stefan" (Author)
ID Džeroski, Sašo, Institut "Jožef Stefan" (Author)
ID Todorovski, Ljupčo, Institut "Jožef Stefan" (Author)
Files:URL URL - Source URL, visit https://www.mdpi.com/2227-7390/12/23/3745
 
.pdf PDF - Presentation file, download (425,51 KB)
MD5: 5E0E54021433F833B999C66AA8345911
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo IJS - Jožef Stefan Institute
Abstract:Equation discovery, also known as symbolic regression, is the field of machine learning that studies algorithms for discovering quantitative laws, expressed as closed-form equations or formulas, in collections of observed data. The latter is expected to come from measurements of physical systems and, therefore, noisy, moving the focus of equation discovery algorithms towards discovering approximate equations. These loosely match the noisy observed data, rendering them inappropriate for applications in mathematics. In this article, we introduce Diofantos, an algorithm for discovering equations in the ring of integers that exactly match the training data. Diofantos is based on a reformulation of the equation discovery task into the task of solving linear Diophantine equations. We empirically evaluate the performance of Diofantos on reconstructing known equations for more than 27,000 sequences from the online encyclopedia of integer sequences, OEIS. Diofantos successfully reconstructs more than 90% of these equations and clearly outperforms SINDy, a state-of-the-art method for discovering approximate equations, that achieves a reconstruction rate of less than 70%.
Keywords:symbolic regression, equation discovery, online encyclopedia of integer sequences
Publication status:Published
Publication version:Version of Record
Submitted for review:03.10.2024
Article acceptance date:24.11.2024
Publication date:28.11.2024
Publisher:MDPI
Year of publishing:2024
Number of pages:str. 1-22
Numbering:Vol. 12, iss. 23, [article no.] 3745
Source:Švica
PID:20.500.12556/DiRROS-21780 New window
UDC:004.8
ISSN on article:2227-7390
DOI:10.3390/math12233745 New window
COBISS.SI-ID:230498307 New window
Copyright:© 2024 by the authors.
Note:Nasl. z nasl. zaslona; Opis vira z dne 27. 3. 2025;
Publication date in DiRROS:27.03.2025
Views:594
Downloads:372
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Record is a part of a journal

Title:Mathematics
Shortened title:Mathematics
Publisher:MDPI AG
ISSN:2227-7390
COBISS.SI-ID:523267865 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0103
Name:Tehnologije znanja

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:GC-0001
Name:Umetna inteligenca za znanost

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:28.11.2024
Applies to:VoR

Secondary language

Language:Slovenian
Keywords:odkrivanje enačb


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