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Parameter identification for symbolic regression using nonlinear least squares

Genetic programming and evolvable machines, 2020-09, Vol.21 (3), p.471-501

2020

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Extending a physics-based constitutive model using genetic programming

Applications in engineering science, 2022-03, Vol.9, p.100080, Article 100080

2022

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Application of symbolic regression for constitutive modeling of plastic deformation

Applications in engineering science, 2021-06, Vol.6, p.100052, Article 100052

2021

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Continuous improvement and adaptation of predictive models in smart manufacturing and model management

IET collaborative intelligent manufacturing, 2021-03, Vol.3 (1), p.48-63

2021

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Prediction of microscopic residual stresses using genetic programming

Applications in engineering science, 2023-09, Vol.15, p.100141, Article 100141

2023

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Data Validation Utilizing Expert Knowledge and Shape Constraints

ACM journal of data and information quality, 2024-06, Vol.16 (2), p.1-27, Article 13

2024

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Comparing Shape-Constrained Regression Algorithms for Data Validation

Computer Aided Systems Theory – EUROCAST 2022, p.147-154

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Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction

IEEE journal of biomedical and health informatics, 2024-05, Vol.28 (5), p.3067-3078

2024

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Shape-Constrained Symbolic Regression with NSGA-III

Computer Aided Systems Theory – EUROCAST 2022, p.164-172

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Smart Manufacturing and Continuous Improvement and Adaptation of Predictive Models

Procedia manufacturing, 2020, Vol.42, p.528-531

2020

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Prediction of stress-strain curves for aluminium alloys using symbolic regression

AIP Conference Proceedings, 2019, Vol.2113 (1)

2019

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A precise symbolic emulator of the linear matter power spectrum

Astronomy and astrophysics (Berlin), 2024-06, Vol.686

2024

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Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs

IEEE transactions on industrial electronics (1982), 2014-11, Vol.61 (11), p.6454-6462

2014

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Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods

Journal of medical systems, 2017-09, Vol.41 (9), p.142-142, Article 142

2017

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Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain

Procedia computer science, 2023, Vol.217, p.796-805

2023

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Better GP benchmarks: community survey results and proposals

Genetic programming and evolvable machines, 2013-03, Vol.14 (1), p.3-29

2013

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Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications

Computer Aided Systems Theory – EUROCAST 2019, p.263-270

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Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems

Applied soft computing, 2018-08, Vol.69, p.610-624

2018

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Multilayer analysis of population diversity in grammatical evolution for symbolic regression

Soft computing (Berlin, Germany), 2020-08, Vol.24 (15), p.11283-11295

2020

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Declarative Modeling and Bayesian Inference of Dark Matter Halos

Computer Aided Systems Theory - EUROCAST 2013, p.195-202

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Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2022, p.304-310

Kronberger, Gabriel

2022

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Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization

Computer Aided Systems Theory – EUROCAST 2022, p.139-146

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Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem

Computer Aided Systems Theory – EUROCAST 2015, p.375-383

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Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming

Computer Aided Systems Theory - EUROCAST 2013, p.308-315

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Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning

Computer Aided Systems Theory – EUROCAST 2015, p.326-333

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Parameter identification for symbolic regression using nonlinear least squares

Extending a physics-based constitutive model using genetic programming

Application of symbolic regression for constitutive modeling of plastic deformation

Continuous improvement and adaptation of predictive models in smart manufacturing and model management

Prediction of microscopic residual stresses using genetic programming

Data Validation Utilizing Expert Knowledge and Shape Constraints

Comparing Shape-Constrained Regression Algorithms for Data Validation

Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction

Shape-Constrained Symbolic Regression with NSGA-III

Smart Manufacturing and Continuous Improvement and Adaptation of Predictive Models

Prediction of stress-strain curves for aluminium alloys using symbolic regression

A precise symbolic emulator of the linear matter power spectrum

Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods

Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain

Better GP benchmarks: community survey results and proposals

Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications

Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems

Multilayer analysis of population diversity in grammatical evolution for symbolic regression

Declarative Modeling and Bayesian Inference of Dark Matter Halos

Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression

Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization

Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem

Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming

Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning

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