SymFormer: End-to-End Symbolic Regression Using Transformer-Based Architecture-Reference-Cited by-同舟云学术

SymFormer: End-to-End Symbolic Regression Using Transformer-Based Architecture

Published:2024 Issue: Volume:12 Page:37840-37849
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Vastl Martin¹,Kulhánek Jonáš¹^ORCID,Kubalík Jiří¹^ORCID,Derner Erik¹^ORCID,Babuška Robert¹^ORCID

Affiliation:

1. Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic

Funder

European Regional Development Fund under the project Robotics for Industry 4.0

Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90140) and through the e-INFRA CZ

European Union’s Horizon Europe research and innovation programme

European Union or the Horizon Europe programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10462113.pdf?arnumber=10462113

Reference40 articles.

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2. Analytical modelling of exoplanet transit specroscopy with dimensional analysis and symbolic regression;Matchev;arXiv:2112.11600,2021

3. Symbolic Regression Methods for Reinforcement Learning

4. Interpretable policies for reinforcement learning by genetic programming;Hein;arXiv:1712.04170,2017

5. Symbolic regression outperforms other models for small data sets;Wilstrup;arXiv:2103.15147,2021

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