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Symbolic Regression

producing a mathematical expression (symbolic expression) that fits a given tabular data.

Papers

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Showing 226–250 of 418 papers

TitleStatusHype
Controllable Neural Symbolic Regression—0
Differentiable Genetic Programming for High-dimensional Symbolic Regression—0
Untangling the Effects of Down-Sampling and Selection in Genetic Programming—0
Priors for symbolic regressionCode0
Data-driven HVAC Control Using Symbolic Regression: Design and Implementation—0
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition—0
All You Need Is Sex for Diversity—0
Context Matters: Adaptive Mutation for GrammarsCode0
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approachCode0
Transformer-based Planning for Symbolic RegressionCode1
Symbolic Regression for PDEs using Pruned Differentiable Programs—0
Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical lawsCode3
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search—0
Online Symbolic Regression with Informative Query—0
Efficient Generator of Mathematical Expressions for Symbolic RegressionCode1
Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions—0
Down-Sampled Epsilon-Lexicase Selection for Real-World Symbolic Regression Problems—0
SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning MethodCode1
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations—0
Learning Symbolic Models for Graph-structured Physical Mechanism—0
Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression—0
Incorporating Background Knowledge in Symbolic Regression using a Computer Algebra System—0
Symbolic expression generation via Variational Auto-Encoder—0
On the functional form of the radial acceleration relationCode1
Discovery of structure-property relations for molecules via hypothesis-driven active learning over the chemical space—0
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