Bandit-Based Monte-Carlo Planning for the Single-Machine Total Weighted Tardiness Scheduling Problem. - Gabriel Kronberger; Roland Braune (EUROCAST, 2007)

Benefits of Plugin-Based Heuristic Optimization Software Systems. - Stefan Wagner 002; Stephan M. Winkler; Erik Pitzer; Gabriel Kronberger; Andreas Beham; Roland Braune; Michael Affenzeller (EUROCAST, 2007)

Metaheuristic Optimization. - Michael Affenzeller; Andreas Beham; Monika Kofler; Gabriel Kronberger; Stefan A. Wagner; Stephan M. Winkler (Hagenberg Research, 2009)

Priority Rule Generation with a Genetic Algorithm to Minimize Sequence Dependent Setup Costs. - Monika Kofler; Stefan Wagner 002; Andreas Beham; Gabriel Kronberger; Michael Affenzeller (EUROCAST, 2009)

On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. - Gabriel Kronberger; Stephan M. Winkler; Michael Affenzeller; Andreas Beham; Stefan Wagner 002 (EUROCAST, 2009)

Model Driven Rapid Prototyping of Heuristic Optimization Algorithms. - Stefan Wagner 002; Gabriel Kronberger; Andreas Beham; Stephan M. Winkler; Michael Affenzeller (EUROCAST, 2009)

On Crossover Success Rate in Genetic Programming with Offspring Selection. - Gabriel Kronberger; Stephan M. Winkler; Michael Affenzeller; Stefan Wagner 002 (EuroGP, 2009)

Application of Symbolic Regression on Blast Furnace and Temper Mill Datasets. - Michael Kommenda; Gabriel Kronberger; Christoph Feilmayr; Leonhard Schickmair; Michael Affenzeller; Stephan M. Winkler; Stefan Wagner 002 (EUROCAST (1), 2011)

Market Basket Analysis of Retail Data: Supervised Learning Approach. - Gabriel Kronberger; Michael Affenzeller (EUROCAST (1), 2011)

Parameter Meta-optimization of Metaheuristic Optimization Algorithms. - Christoph Neumüller; Stefan Wagner 002; Gabriel Kronberger; Michael Affenzeller (EUROCAST (1), 2011)

Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling. - Stephan M. Winkler; Michael Affenzeller; Gabriel Kronberger; Michael Kommenda; Stefan Wagner 002; Witold Jacak; Herbert Stekel (EUROCAST (1), 2011)

Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process. - Alexandru-Ciprian Zavoianu; Gabriel Kronberger; Michael Kommenda; Daniela Zaharie; Michael Affenzeller (EUROCAST (1), 2011)

Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset. - Michael Kommenda; Gabriel Kronberger; Christoph Feilmayr; Michael Affenzeller (EvoApplications (1), 2011)

Macro-economic Time Series Modeling and Interaction Networks. - Gabriel Kronberger; Stefan Fink; Michael Kommenda; Michael Affenzeller (EvoApplications (2), 2011)

Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. - Gabriel Kronberger; Michael Kommenda; Michael Affenzeller (GECCO (Companion), 2011)

Algorithm and experiment design with heuristiclab: an open source optimization environment for research and education. - Stefan Wagner 002; Gabriel Kronberger (GECCO (Companion), 2011)

Combining Data Mining and Ontology Engineering to Enrich Ontologies and Linked Data. - Mathieu d'Aquin; Gabriel Kronberger; Mari Carmen Suárez-Figueroa (KNOW@LOD, 2012)

On the architecture and implementation of tree-based genetic programming in HeuristicLab. - Michael Kommenda; Gabriel Kronberger; Stefan Wagner 002; Stephan M. Winkler; Michael Affenzeller (GECCO (Companion), 2012)

Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education. - Stefan Wagner 002; Gabriel Kronberger (GECCO (Companion), 2012)

Knowledge Discovery through Symbolic Regression with HeuristicLab. - Gabriel Kronberger; Stefan Wagner 002; Michael Kommenda; Andreas Beham; Andreas Scheibenpflug; Michael Affenzeller (ECML/PKDD (2), 2012)

Nonlinear Least Squares Optimization of Constants in Symbolic Regression. - Michael Kommenda; Michael Affenzeller; Gabriel Kronberger; Stephan M. Winkler (EUROCAST (1), 2013)

Declarative Modeling and Bayesian Inference of Dark Matter Halos. - Gabriel Kronberger (EUROCAST (1), 2013)

Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming. - Gabriel Kronberger; Michael Kommenda (EUROCAST (1), 2013)

Visualization of genetic lineages and inheritance information in genetic programming. - Bogdan Burlacu; Michael Affenzeller; Michael Kommenda; Stephan M. Winkler; Gabriel Kronberger (GECCO (Companion), 2013)

Effects of constant optimization by nonlinear least squares minimization in symbolic regression. - Michael Kommenda; Gabriel Kronberger; Stephan M. Winkler; Michael Affenzeller; Stefan Wagner 002 (GECCO (Companion), 2013)

GPDL: a framework-independent problem definition language for grammar-guided genetic programming. - Gabriel Kronberger; Michael Kommenda; Stefan Wagner 002; Heinz Dobler (GECCO (Companion), 2013)

Gaining Deeper Insights in Symbolic Regression. - Michael Affenzeller; Stephan M. Winkler; Gabriel Kronberger; Michael Kommenda; Bogdan Burlacu; Stefan Wagner 002 (GPTP, 2013)

Better GP benchmarks: community survey results and proposals. - David Robert White; James McDermott; Mauro Castelli; Luca Manzoni; Brian W. Goldman; Gabriel Kronberger; Wojciech Jaskowski; Una-May O'Reilly; Sean Luke (Genet. Program. Evolvable Mach., 2013)

On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer. - Stephan M. Winkler; Michael Affenzeller; Gabriel Kronberger; Michael Kommenda; Stefan Wagner 002; Viktoria Dorfer; Witold Jacak; Herbert Stekel (Int. J. Simul. Process. Model., 2013)

Scripting and framework integration in heuristic optimization environments. - Andreas Beham; Johannes Karder; Gabriel Kronberger; Stefan Wagner 002; Michael Kommenda; Andreas Scheibenpflug (GECCO (Companion), 2014)

Genetic programming with data migration for symbolic regression. - Michael Kommenda; Michael Affenzeller; Bogdan Burlacu; Gabriel Kronberger; Stephan M. Winkler (GECCO (Companion), 2014)

Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. - Stephan M. Winkler; Michael Affenzeller; Gabriel Kronberger; Michael Kommenda; Bogdan Burlacu; Stefan Wagner 002 (GPTP, 2014)

Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs. - Gerd Bramerdorfer; Stephan M. Winkler; Michael Kommenda; Günther Weidenholzer; Siegfried Silber; Gabriel Kronberger; Michael Affenzeller; Wolfgang Amrhein (IEEE Trans. Ind. Electron., 2014)

Complexity Measures for Multi-objective Symbolic Regression. - Michael Kommenda; Andreas Beham; Michael Affenzeller; Gabriel Kronberger (EUROCAST, 2015)

Using Contextual Information in Sequential Search for Grammatical Optimization Problems. - Gabriel Kronberger; Michael Kommenda; Stephan M. Winkler; Michael Affenzeller (EUROCAST, 2015)

Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem. - Erik Pitzer; Gabriel Kronberger (EUROCAST, 2015)

Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning. - Stephan M. Winkler; Gabriel Kronberger; Michael Kommenda; Stefan Fink; Michael Affenzeller (EUROCAST, 2015)

Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming. - Michael Kommenda; Gabriel Kronberger; Michael Affenzeller; Stephan M. Winkler; Bogdan Burlacu (GPTP, 2015)

Methods for Genealogy and Building Block Analysis in Genetic Programming. - Bogdan Burlacu; Michael Affenzeller; Stephan M. Winkler; Michael Kommenda; Gabriel Kronberger (Computational Intelligence and Efficiency in Engineering Systems, 2015)

Multi-Population Genetic Programming with Data Migration for Symbolic Regression. - Michael Kommenda; Michael Affenzeller; Gabriel Kronberger; Bogdan Burlacu; Stephan M. Winkler (Computational Intelligence and Efficiency in Engineering Systems, 2015)

Search Strategies for Grammatical Optimization Problems - Alternatives to Grammar-Guided Genetic Programming. - Gabriel Kronberger; Michael Kommenda (Computational Intelligence and Efficiency in Engineering Systems, 2015)

Concise Supply-Chain Simulation Optimization for Large Scale Logistic Networks. - Erik Pitzer; Gabriel Kronberger (Computational Intelligence and Efficiency in Engineering Systems, 2015)

Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring. - J. Manuel Colmenar; Stephan M. Winkler; Gabriel Kronberger; Esther Maqueda; Marta Botella; José Ignacio Hidalgo (GECCO (Companion), 2016)

Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression. - Stephan M. Winkler; Michael Affenzeller; Bogdan Burlacu; Gabriel Kronberger; Michael Kommenda; Philipp Fleck (GPTP, 2016)

Robust Fuzzy Modeling and Symbolic Regression for Establishing Accurate and Interpretable Prediction Models in Supervising Tribological Systems. - Edwin Lughofer; Gabriel Kronberger; Michael Kommenda; Susanne Saminger-Platz; Andreas Promberger; Falk Nickel; Stephan M. Winkler; Michael Affenzeller (IJCCI (FCTA), 2016)

Heterogeneous model ensembles for short-term prediction of stock market trends. - Stephan M. Winkler; Bonifacio Castaño; Sergio Luengo-Sanchez; Susanne Schaller; Gabriel Kronberger; Michael Affenzeller (Int. J. Simul. Process. Model., 2016)

Offspring Selection Genetic Algorithm Revisited: Improvements in Efficiency by Early Stopping Criteria in the Evaluation of Unsuccessful Individuals. - Michael Affenzeller; Bogdan Burlacu; Stephan M. Winkler; Michael Kommenda; Gabriel Kronberger; Stefan Wagner 002 (EUROCAST (1), 2017)

Analysis of Schema Frequencies in Genetic Programming. - Bogdan Burlacu; Michael Affenzeller; Michael Kommenda; Gabriel Kronberger; Stephan M. Winkler (EUROCAST (1), 2017)

Glucose Prognosis by Grammatical Evolution. - José Ignacio Hidalgo; J. Manuel Colmenar; Gabriel Kronberger; Stephan M. Winkler (EUROCAST (1), 2017)

Optimization Networks for Integrated Machine Learning. - Michael Kommenda; Johannes Karder; Andreas Beham; Bogdan Burlacu; Gabriel Kronberger; Stefan Wagner 002; Michael Affenzeller (EUROCAST (1), 2017)

Measures for the Evaluation and Comparison of Graphical Model Structures. - Gabriel Kronberger; Bogdan Burlacu; Michael Kommenda; Stephan M. Winkler; Michael Affenzeller (EUROCAST (1), 2017)

Dynamic observation of genotypic and phenotypic diversity for different symbolic regression GP variants. - Michael Affenzeller; Stephan M. Winkler; Bogdan Burlacu; Gabriel Kronberger; Michael Kommenda; Stefan Wagner 002 (GECCO (Companion), 2017)

Schema Analysis in Tree-Based Genetic Programming. - Bogdan Burlacu; Michael Affenzeller; Michael Kommenda; Gabriel Kronberger; Stephan M. Winkler (GPTP, 2017)

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. - José Ignacio Hidalgo; J. Manuel Colmenar; Gabriel Kronberger; Stephan M. Winkler; Oscar Garnica; Juan Lanchares (J. Medical Syst., 2017)

Identification of Models for Glucose Blood Values in Diabetics by Grammatical Evolution. - José Ignacio Hidalgo; J. Manuel Colmenar; J. Manuel Velasco; Gabriel Kronberger; Stephan M. Winkler; Oscar Garnica; Juan Lanchares (Handbook of Grammatical Evolution, 2018)

Predicting friction system performance with symbolic regression and genetic programming with factor variables. - Gabriel Kronberger; Michael Kommenda; Andreas Promberger; Falk Nickel (GECCO, 2018)

Cluster Analysis of a Symbolic Regression Search Space. - Gabriel Kronberger; Lukas Kammerer; Bogdan Burlacu; Stephan M. Winkler; Michael Kommenda; Michael Affenzeller (GPTP, 2018)

Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. - Gabriel Kronberger; Michael Kommenda; Edwin Lughofer; Susanne Saminger-Platz; Andreas Promberger; Falk Nickel; Stephan M. Winkler; Michael Affenzeller (Appl. Soft Comput., 2018)

Using Ontologies to Express Prior Knowledge for Genetic Programming. - Stefan Prieschl; Dominic Girardi; Gabriel Kronberger (CD-MAKE, 2019)

Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. - Bogdan Burlacu; Michael Affenzeller; Gabriel Kronberger; Michael Kommenda (CEC, 2019)

Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. - Florian Bachinger; Gabriel Kronberger (EUROCAST (1), 2019)

Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. - Bogdan Burlacu; Lukas Kammerer; Michael Affenzeller; Gabriel Kronberger (EUROCAST (1), 2019)

Data Aggregation for Reducing Training Data in Symbolic Regression. - Lukas Kammerer; Gabriel Kronberger; Michael Kommenda (EUROCAST (1), 2019)

Identification of Dynamical Systems Using Symbolic Regression. - Gabriel Kronberger; Lukas Kammerer; Michael Kommenda (EUROCAST (1), 2019)

Concept Drift Detection with Variable Interaction Networks. - Jan Zenisek; Gabriel Kronberger; Josef Wolfartsberger; Norbert Wild; Michael Affenzeller (EUROCAST (1), 2019)

Parsimony measures in multi-objective genetic programming for symbolic regression. - Bogdan Burlacu; Gabriel Kronberger; Michael Kommenda; Michael Affenzeller (GECCO (Companion), 2019)

Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. - Lukas Kammerer; Gabriel Kronberger; Bogdan Burlacu; Stephan M. Winkler; Michael Kommenda; Michael Affenzeller (GPTP, 2019)

Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. - David Joedicke; Gabriel Kronberger; José Manuel Colmenar; Stephan M. Winkler; José Manuel Velasco; Sergio Contador; José Ignacio Hidalgo (KDH@ECAI, 2020)

Operon C++: an efficient genetic programming framework for symbolic regression. - Bogdan Burlacu; Gabriel Kronberger; Michael Kommenda (GECCO Companion, 2020)

Parameter identification for symbolic regression using nonlinear least squares. - Michael Kommenda; Bogdan Burlacu; Gabriel Kronberger; Michael Affenzeller (Genet. Program. Evolvable Mach., 2020)

Multilayer analysis of population diversity in grammatical evolution for symbolic regression. - Gabriel Kronberger; J. Manuel Colmenar; Stephan M. Winkler; José Ignacio Hidalgo (Soft Comput., 2020)

Estimation of Grain-Level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 Using Genetic Programming. - Laura Millán; Gabriel Kronberger; José Ignacio Hidalgo; Ricardo Fernández; Oscar Garnica; Gaspar González-Doncel (EvoApplications, 2021)

Empirical analysis of variance for genetic programming based symbolic regression. - Lukas Kammerer; Gabriel Kronberger; Stephan M. Winkler (GECCO Companion, 2021)

Using Shape Constraints for Improving Symbolic Regression Models. - Christian Haider; Fabrício Olivetti de França; Bogdan Burlacu; Gabriel Kronberger (CoRR, 2021)

Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming. - Gabriel Kronberger; Evgeniya Kabliman; Johannes Kronsteiner; Michael Kommenda (CoRR, 2021)

Comparing Shape-Constrained Regression Algorithms for Data Validation. - Florian Bachinger; Gabriel Kronberger (EUROCAST, 2022)

Shape-Constrained Symbolic Regression with NSGA-III. - Christian Haider; Gabriel Kronberger (EUROCAST, 2022)

Identifying Differential Equations for the Prediction of Blood Glucose using Sparse Identification of Nonlinear Systems. - David Joedicke; Daniel Parra; Gabriel Kronberger; Stephan M. Winkler (EUROCAST, 2022)

Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. - Lukas Kammerer; Gabriel Kronberger; Michael Kommenda (EUROCAST, 2022)

Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. - Christian Haider; Fabrício Olivetti de França; Gabriel Kronberger; Bogdan Burlacu (GECCO, 2022)

Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. - Bogdan Burlacu; Michael Kommenda; Gabriel Kronberger; Stephan M. Winkler; Michael Affenzeller (GPTP, 2022)

Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain. - Hannah Janout; Thomas Paier; Carina Ringelhahn; Michael Heckmann; Andreas Haghofer; Gabriel Kronberger; Stephan Winkler 001 (ISM, 2022)

Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. - Gabriel Kronberger (SYNASC, 2022)

Steel Phase Kinetics Modeling using Symbolic Regression. - David Piringer; Bernhard Bloder; Gabriel Kronberger (SYNASC, 2022)

Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression. - Martin Steiger; Hans Georg Brachtendorf; Gabriel Kronberger (SYNASC, 2022)

Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles. - Fabrício Olivetti de França; Gabriel Kronberger (CoRR, 2022)

Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems. - David Jödicke; Daniel Parra; Gabriel Kronberger; Stephan M. Winkler (CoRR, 2022)

Shape-Constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. - Gabriel Kronberger; Fabrício Olivetti de França; Bogdan Burlacu; Christian Haider; Michael Kommenda (Evol. Comput., 2022)

Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. - Fabrício Olivetti de França; Gabriel Kronberger (GECCO, 2023)

Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. - Christian Haider; Fabrício Olivetti de França; Bogdan Burlacu; Florian Bachinger; Gabriel Kronberger; Michael Affenzeller (GPTP, 2023)

Shape-constrained multi-objective genetic programming for symbolic regression. - Christian Haider; Fabrício Olivetti de França; Bogdan Burlacu; Gabriel Kronberger (Appl. Soft Comput., 2023)

A precise symbolic emulator of the linear matter power spectrum. - Deaglan J. Bartlett; Lukas Kammerer; Gabriel Kronberger; Harry Desmond; Pedro G. Ferreira; Benjamin D. Wandelt; Bogdan Burlacu; David Alonso; Matteo Zennaro (CoRR, 2023)

A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming. - Yousef A. Radwan; Gabriel Kronberger; Stephan Winkler 001 (EUROCAST (1), 2024)

Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. - Patrick E. Leser; Geoffrey F. Bomarito; Gabriel Kronberger; Fabrício Olivetti de França (GECCO Companion, 2024)

The Inefficiency of Genetic Programming for Symbolic Regression. - Gabriel Kronberger; Fabrício Olivetti de França; Harry Desmond; Deaglan J. Bartlett; Lukas Kammerer (PPSN (1), 2024)

The Inefficiency of Genetic Programming for Symbolic Regression - Extended Version. - Gabriel Kronberger; Fabrício Olivetti de França; Harry Desmond; Deaglan J. Bartlett; Lukas Kammerer (CoRR, 2024)

Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction. - Daniel Parra; David Joedicke; J. Manuel Velasco; Gabriel Kronberger; José Ignacio Hidalgo (IEEE J. Biomed. Health Informatics, 2024)

Data Validation Utilizing Expert Knowledge and Shape Constraints. - Florian Bachinger; Lisa Ehrlinger; Gabriel Kronberger; Wolfram Wöß (ACM J. Data Inf. Qual., 2024)

rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models. - Fabrício Olivetti de França; Gabriel Kronberger (GECCO, 2025)

Improving Genetic Programming for Symbolic Regression with Equality Graphs. - Fabrício Olivetti de França; Gabriel Kronberger (GECCO, 2025)

Effects of reducing redundant parameters in parameter optimization for symbolic regression using genetic programming. - Gabriel Kronberger; Fabrício Olivetti de França (J. Symb. Comput., 2025)

syren-baryon: Analytic emulators for the impact of baryons on the matter power spectrum. - Lukas Kammerer; Deaglan J. Bartlett; Gabriel Kronberger; Harry Desmond; Pedro G. Ferreira (CoRR, 2025)