Results 11 to 20 of about 2,854,398 (286)

Vertical Symbolic Regression [PDF]

CoRR, 2023
Automating scientific discovery has been a grand goal of Artificial Intelligence (AI) and will bring tremendous societal impact. Learning symbolic expressions from experimental data is a vital step in AI-driven scientific discovery.
Jiang, Nan, Nasim, Md, Xue, Yexiang
core   +5 more sources

Symbolic-Regression Boosting

Genetic Programming and Evolvable Machines, 2022
Modifying standard gradient boosting by replacing the embedded weak learner in favor of a strong(er) one, we present SyRBo: Symbolic-Regression Boosting.
Sipper, Moshe, Moore, Jason H
core   +5 more sources

Deep Generative Symbolic Regression [PDF]

CoRR, 2023
Symbolic regression (SR) aims to discover concise closed-form mathematical equations from data, a task fundamental to scientific discovery. However, the problem is highly challenging because closed-form equations lie in a complex combinatorial search ...
Qian, Zhaozhi, Holt, Samuel, van der Schaar, Mihaela   +2 more
core   +6 more sources

Glyph: Symbolic Regression Tools

Journal of Open Research Software, 2019
We present Glyph – a Python package for genetic programming based symbolic regression. Glyph is designed for usage in numerical simulations as well as real world experiments.
Markus Quade, Julien Gout, Markus Abel
doaj   +6 more sources

Class Symbolic Regression: Gotta Fit ’Em All

The Astrophysical Journal Letters
We introduce “Class Symbolic Regression” (Class SR), the first framework for automatically finding a single analytical functional form that accurately fits multiple data sets—each realization being governed by its own (possibly) unique set of fitting ...
Wassim Tenachi, Rodrigo Ibata, Thibaut L. François, Foivos I. Diakogiannis   +3 more
doaj   +3 more sources

ISR: Invertible Symbolic Regression [PDF]

CoRR
We introduce an Invertible Symbolic Regression (ISR) method. It is a machine learning technique that generates analytical relationships between inputs and outputs of a given dataset via invertible maps (or architectures).
Sadr, Mohsen, Khojasteh, Mohammad Javad, Tohme, Tony, Meyer, Florian, Youcef-Toumi, Kamal   +4 more
core   +4 more sources

Symbolic Regression Approaches for the Direct Calculation of Pipe Diameter [PDF]

Axioms, 2023
This study provides novel and accurate symbolic regression-based solutions for the calculation of pipe diameter when flow rate and pressure drop (head loss) are known, together with the length of the pipe, absolute inner roughness of the pipe, and ...
Dejan Brkić, Pavel Praks, Renáta Praksová, Tomáš Kozubek   +3 more
doaj   +4 more sources

Dimension Reduction for Symbolic Regression

Proceedings of the AAAI Conference on Artificial Intelligence
Solutions of symbolic regression problems are expressions that are composed of input variables and operators from a finite set of function symbols. One measure for evaluating symbolic regression algorithms is their ability to recover formulae, up to ...
Giesen, Joachim, Kahlmeyer, Paul, Fischer, Markus   +2 more
core   +3 more sources

Priors for symbolic regression

Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023
8+2 pages, 2 figures.
Bartlett, D, Desmond, H, Ferreira, P
openaire   +4 more sources

Interactive symbolic regression with co-design mechanism through offline reinforcement learning. [PDF]

Nat Commun
Symbolic Regression holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for previous online search methods ...
Tian Y, Zhou W, Viscione M, Dong H, Kammer DS, Fink O.   +5 more
europepmc   +2 more sources