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Symbolic Regression Driven by Training Data and Prior Knowledge

Symbolic Regression Driven by Training Data and Prior Knowledge

Annual Conference on Genetic and Evolutionary Computation (GECCO), 2020
24 April 2020
Jiří Kubalík
Erik Derner
Robert Babuška
ArXiv (abs)PDFHTML

Papers citing "Symbolic Regression Driven by Training Data and Prior Knowledge"

15 / 15 papers shown
Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowledge via Abductive Inference with AI-Noether
Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowledge via Abductive Inference with AI-Noether
Karan Srivastava
S. Dash
Ryan Cory-Wright
Barry Trager
L. Horesh
Lior Horesh
182
1
0
26 Sep 2025
The Need for Verification in AI-Driven Scientific Discovery
The Need for Verification in AI-Driven Scientific Discovery
Cristina Cornelio
Takuya Ito
Ryan Cory-Wright
S. Dash
L. Horesh
237
4
0
01 Sep 2025
Neuro-Evolutionary Approach to Physics-Aware Symbolic Regression
Neuro-Evolutionary Approach to Physics-Aware Symbolic RegressionAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2025
Jiří Kubalík
Robert Babuška
356
0
0
23 Apr 2025
A Comparison of Recent Algorithms for Symbolic Regression to Genetic
  Programming
A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming
Yousef A. Radwan
G. Kronberger
Stephan M. Winkler
OffRL
361
11
0
05 Jun 2024
Shape Constraints in Symbolic Regression using Penalized Least Squares
Shape Constraints in Symbolic Regression using Penalized Least Squares
Viktor Martinek
J. Reuter
Ophelia Frotscher
Sanaz Mostaghim
Markus Richter
Roland Herzog
248
3
0
31 May 2024
A Novel ML-driven Test Case Selection Approach for Enhancing the
  Performance of Grammatical Evolution
A Novel ML-driven Test Case Selection Approach for Enhancing the Performance of Grammatical Evolution
Krishn Kumar Gupt
Meghana Kshirsagar
D. Dias
Joseph P. Sullivan
Conor Ryan
61
0
0
21 Dec 2023
Evolving Scientific Discovery by Unifying Data and Background Knowledge
  with AI Hilbert
Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI HilbertNature Communications (Nat. Commun.), 2023
Ryan Cory-Wright
Cristina Cornelio
S. Dash
Bachir El Khadir
L. Horesh
411
25
0
18 Aug 2023
Toward Physically Plausible Data-Driven Models: A Novel Neural Network
  Approach to Symbolic Regression
Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic RegressionIEEE Access (IEEE Access), 2023
Jiří Kubalík
Erik Derner
Robert Babuška
263
20
0
01 Feb 2023
Shape-constrained Symbolic Regression with NSGA-III
Shape-constrained Symbolic Regression with NSGA-IIIInternational Conference/Workshop on Computer Aided Systems Theory (EUROCAST), 2022
C. Haider
151
3
0
28 Sep 2022
SymFormer: End-to-end symbolic regression using transformer-based
  architecture
SymFormer: End-to-end symbolic regression using transformer-based architectureIEEE Access (IEEE Access), 2022
Martin Vastl
Jonáš Kulhánek
Jiří Kubalík
Erik Derner
Robert Babuška
496
85
0
31 May 2022
Evolvability Degeneration in Multi-Objective Genetic Programming for
  Symbolic Regression
Evolvability Degeneration in Multi-Objective Genetic Programming for Symbolic RegressionAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2022
Dazhuang Liu
M. Virgolin
Tanja Alderliesten
Peter A. N. Bosman
321
14
0
14 Feb 2022
AI Descartes: Combining Data and Theory for Derivable Scientific
  Discovery
AI Descartes: Combining Data and Theory for Derivable Scientific Discovery
Cristina Cornelio
S. Dash
V. Austel
Tyler R. Josephson
Joao Goncalves
K. Clarkson
N. Megiddo
Bachir El Khadir
L. Horesh
AI4CE
397
8
0
03 Sep 2021
Using Shape Constraints for Improving Symbolic Regression Models
Using Shape Constraints for Improving Symbolic Regression Models
C. Haider
F. O. França
Bogdan Burlacu
G. Kronberger
158
6
0
20 Jul 2021
Logic Guided Genetic Algorithms
Logic Guided Genetic Algorithms
D. Ashok
Joseph Scott
Zakaria Patel
Maysum Panju
Vijay Ganesh
233
14
0
21 Oct 2020
Symbolic Regression Methods for Reinforcement Learning
Symbolic Regression Methods for Reinforcement Learning
Jiří Kubalík
Erik Derner
J. Žegklitz
Robert Babuška
OffRL
218
34
0
22 Mar 2019
1
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