Gabriel Kronberger

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 73

Top Venues

Publications

Daniel Parra, David Joedicke, J. Manuel Velasco, Gabriel Kronberger, José Ignacio Hidalgo
Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction. IEEE J. Biomed. Health Informatics 28 (5) (2024)
Florian Bachinger, Lisa Ehrlinger, Gabriel Kronberger, Wolfram Wöß
Data Validation Utilizing Expert Knowledge and Shape Constraints. ACM J. Data Inf. Qual. 16 (2) (2024)
Patrick E. Leser, Geoffrey F. Bomarito, Gabriel Kronberger, Fabrício Olivetti de França
Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression. GECCO Companion (2024)
Gabriel Kronberger, Fabrício Olivetti de França, Harry Desmond, Deaglan J. Bartlett, Lukas Kammerer
The Inefficiency of Genetic Programming for Symbolic Regression - Extended Version. CoRR (2024)
Yousef A. Radwan, Gabriel Kronberger, Stephan M. Winkler
A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming. CoRR (2024)
Deaglan J. Bartlett, Lukas Kammerer, Gabriel Kronberger, Harry Desmond, Pedro G. Ferreira, Benjamin D. Wandelt, Bogdan Burlacu, David Alonso, Matteo Zennaro
A precise symbolic emulator of the linear matter power spectrum. CoRR (2023)
Hannah Janout, Thomas Paier, Carina Ringelhahn, Michael Heckmann, Andreas Haghofer, Gabriel Kronberger, Stephan Winkler
Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain. ISM (2023)
Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Florian Bachinger, Gabriel Kronberger, Michael Affenzeller
Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. GPTP (2023)
Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Gabriel Kronberger
Shape-constrained multi-objective genetic programming for symbolic regression. Appl. Soft Comput. 132 (2023)
Fabrício Olivetti de França, Gabriel Kronberger
Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. GECCO (2023)
Daniel Parra, David Joedicke, J. Manuel Velasco, Gabriel Kronberger, José Ignacio Hidalgo
Learning Difference Equations with Structured Grammatical Evolution for Postprandial Glycaemia Prediction. CoRR (2023)
David Piringer, Bernhard Bloder, Gabriel Kronberger
Steel Phase Kinetics Modeling using Symbolic Regression. SYNASC (2022)
Fabrício Olivetti de França, Gabriel Kronberger
Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles. CoRR (2022)
David Jödicke, Daniel Parra, Gabriel Kronberger, Stephan M. Winkler
Identifying Differential Equations to predict Blood Glucose using Sparse Identification of Nonlinear Systems. CoRR (2022)
Gabriel Kronberger
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. CoRR (2022)
David Piringer, Bernhard Bloder, Gabriel Kronberger
Steel Phase Kinetics Modeling using Symbolic Regression. CoRR (2022)
Christian Haider, Gabriel Kronberger
Shape-Constrained Symbolic Regression with NSGA-III. EUROCAST (2022)
Martin Steiger, Hans Georg Brachtendorf, Gabriel Kronberger
Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression. SYNASC (2022)
Christian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. GECCO (2022)
David Joedicke, Daniel Parra, Gabriel Kronberger, Stephan M. Winkler
Identifying Differential Equations for the Prediction of Blood Glucose using Sparse Identification of Nonlinear Systems. EUROCAST (2022)
Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda
Shape-Constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. Evol. Comput. 30 (1) (2022)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. EUROCAST (2022)
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. CoRR (2022)
Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data. GPTP (2022)
Florian Bachinger, Gabriel Kronberger
Comparing Shape-Constrained Regression Algorithms for Data Validation. EUROCAST (2022)
Florian Bachinger, Gabriel Kronberger
Comparing Shape-Constrained Regression Algorithms for Data Validation. CoRR (2022)
Gabriel Kronberger
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression. SYNASC (2022)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization. CoRR (2022)
Erik Pitzer, Gabriel Kronberger
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-valued Optimization Problem. CoRR (2021)
Gabriel Kronberger, Lukas Kammerer, Michael Kommenda
Identification of Dynamical Systems using Symbolic Regression. CoRR (2021)
Laura Millán, Gabriel Kronberger, José Ignacio Hidalgo, Ricardo Fernández, Oscar Garnica, Gaspar González-Doncel
Estimation of Grain-Level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 Using Genetic Programming. EvoApplications (2021)
Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller
Concept Drift Detection with Variable Interaction Networks. CoRR (2021)
Lukas Kammerer, Gabriel Kronberger, Stephan M. Winkler
Empirical analysis of variance for genetic programming based symbolic regression. GECCO Companion (2021)
Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner, Michael Kommenda
Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming. CoRR (2021)
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Cluster Analysis of a Symbolic Regression Search Space. CoRR (2021)
Gabriel Kronberger, Fabrício Olivetti de França, Bogdan Burlacu, Christian Haider, Michael Kommenda
Shape-constrained Symbolic Regression - Improving Extrapolation with Prior Knowledge. CoRR (2021)
Florian Bachinger, Gabriel Kronberger
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. CoRR (2021)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. CoRR (2021)
Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. CoRR (2021)
Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. CoRR (2021)
Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger
Complexity Measures for Multi-objective Symbolic Regression. CoRR (2021)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Data Aggregation for Reducing Training Data in Symbolic Regression. CoRR (2021)
Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel
Predicting Friction System Performance with Symbolic Regression and Genetic Programming with Factor Variables. CoRR (2021)
Christian Haider, Fabrício Olivetti de França, Bogdan Burlacu, Gabriel Kronberger
Using Shape Constraints for Improving Symbolic Regression Models. CoRR (2021)
Michael Kommenda, Bogdan Burlacu, Gabriel Kronberger, Michael Affenzeller
Parameter identification for symbolic regression using nonlinear least squares. Genet. Program. Evolvable Mach. 21 (3) (2020)
Gabriel Kronberger, J. Manuel Colmenar, Stephan M. Winkler, José Ignacio Hidalgo
Multilayer analysis of population diversity in grammatical evolution for symbolic regression. Soft Comput. 24 (15) (2020)
David Joedicke, Gabriel Kronberger, José Manuel Colmenar, Stephan M. Winkler, José Manuel Velasco, Sergio Contador, José Ignacio Hidalgo
Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. KDH@ECAI (2020)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda
Operon C++: an efficient genetic programming framework for symbolic regression. GECCO Companion (2020)
Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CoRR (2019)
Jan Zenisek, Gabriel Kronberger, Josef Wolfartsberger, Norbert Wild, Michael Affenzeller
Concept Drift Detection with Variable Interaction Networks. EUROCAST (1) (2019)
Stefan Prieschl, Dominic Girardi, Gabriel Kronberger
Using Ontologies to Express Prior Knowledge for Genetic Programming. CD-MAKE (2019)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) (2019)
Lukas Kammerer, Gabriel Kronberger, Michael Kommenda
Data Aggregation for Reducing Training Data in Symbolic Regression. EUROCAST (1) (2019)
Bogdan Burlacu, Lukas Kammerer, Michael Affenzeller, Gabriel Kronberger
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression. EUROCAST (1) (2019)
Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure. CEC (2019)
Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. GPTP (2019)
Florian Bachinger, Gabriel Kronberger
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications. EUROCAST (1) (2019)
Gabriel Kronberger, Lukas Kammerer, Michael Kommenda
Identification of Dynamical Systems Using Symbolic Regression. EUROCAST (1) (2019)
Gabriel Kronberger, Michael Kommenda, Edwin Lughofer, Susanne Saminger-Platz, Andreas Promberger, Falk Nickel, Stephan M. Winkler, Michael Affenzeller
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. Appl. Soft Comput. 69 (2018)
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Cluster Analysis of a Symbolic Regression Search Space. GPTP (2018)
Gabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel
Predicting friction system performance with symbolic regression and genetic programming with factor variables. GECCO (2018)
Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Stefan Wagner
Dynamic observation of genotypic and phenotypic diversity for different symbolic regression GP variants. GECCO (Companion) (2017)
José Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger, Stephan M. Winkler
Glucose Prognosis by Grammatical Evolution. EUROCAST (1) (2017)
Michael Affenzeller, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Gabriel Kronberger, Stefan Wagner
Offspring Selection Genetic Algorithm Revisited: Improvements in Efficiency by Early Stopping Criteria in the Evaluation of Unsuccessful Individuals. EUROCAST (1) (2017)
José Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger, Stephan M. Winkler, Oscar Garnica, Juan Lanchares
Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. J. Medical Syst. 41 (9) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Schema Analysis in Tree-Based Genetic Programming. GPTP (2017)
Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
Measures for the Evaluation and Comparison of Graphical Model Structures. EUROCAST (1) (2017)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler
Analysis of Schema Frequencies in Genetic Programming. EUROCAST (1) (2017)
Michael Kommenda, Johannes Karder, Andreas Beham, Bogdan Burlacu, Gabriel Kronberger, Stefan Wagner, Michael Affenzeller
Optimization Networks for Integrated Machine Learning. EUROCAST (1) (2017)
Edwin Lughofer, Gabriel Kronberger, Michael Kommenda, Susanne Saminger-Platz, Andreas Promberger, Falk Nickel, Stephan M. Winkler, Michael Affenzeller
Robust Fuzzy Modeling and Symbolic Regression for Establishing Accurate and Interpretable Prediction Models in Supervising Tribological Systems. IJCCI (FCTA) (2016)
Stephan M. Winkler, Bonifacio Castaño, Sergio Luengo-Sanchez, Susanne Schaller, Gabriel Kronberger, Michael Affenzeller
Heterogeneous model ensembles for short-term prediction of stock market trends. Int. J. Simul. Process. Model. 11 (6) (2016)
J. Manuel Colmenar, Stephan M. Winkler, Gabriel Kronberger, Esther Maqueda, Marta Botella, José Ignacio Hidalgo
Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring. GECCO (Companion) (2016)
Stephan M. Winkler, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Philipp Fleck
Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression. GPTP (2016)
Gabriel Kronberger, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
Using Contextual Information in Sequential Search for Grammatical Optimization Problems. EUROCAST (2015)
Michael Kommenda, Andreas Beham, Michael Affenzeller, Gabriel Kronberger
Complexity Measures for Multi-objective Symbolic Regression. EUROCAST (2015)
Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Stefan Fink, Michael Affenzeller
Dynamics of Predictability and Variable Influences Identified in Financial Data Using Sliding Window Machine Learning. EUROCAST (2015)
Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu
Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming. GPTP (2015)
Erik Pitzer, Gabriel Kronberger
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem. EUROCAST (2015)
Andreas Beham, Johannes Karder, Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Scheibenpflug
Scripting and framework integration in heuristic optimization environments. GECCO (Companion) (2014)
Gerd Bramerdorfer, Stephan M. Winkler, Michael Kommenda, Günther Weidenholzer, Siegfried Silber, Gabriel Kronberger, Michael Affenzeller, Wolfgang Amrhein
Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs. IEEE Trans. Ind. Electron. 61 (11) (2014)
Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. GPTP (2014)
Michael Kommenda, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Stephan M. Winkler
Genetic programming with data migration for symbolic regression. GECCO (Companion) (2014)
Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr, Michael Affenzeller
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset. CoRR (2013)
Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Viktoria Dorfer, Witold Jacak, Herbert Stekel
On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer. Int. J. Simul. Process. Model. 8 (1) (2013)
Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Stephan M. Winkler
Nonlinear Least Squares Optimization of Constants in Symbolic Regression. EUROCAST (1) (2013)
Michael Affenzeller, Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
Gaining Deeper Insights in Symbolic Regression. GPTP (2013)
Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Stefan Wagner
Effects of constant optimization by nonlinear least squares minimization in symbolic regression. GECCO (Companion) (2013)
David Robert White, James McDermott, Mauro Castelli, Luca Manzoni, Brian W. Goldman, Gabriel Kronberger, Wojciech Jaskowski, Una-May O'Reilly, Sean Luke
Better GP benchmarks: community survey results and proposals. Genet. Program. Evolvable Mach. 14 (1) (2013)
Gabriel Kronberger, Michael Kommenda
Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming. EUROCAST (1) (2013)
Gabriel Kronberger, Michael Kommenda
Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming CoRR (2013)
Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller, Andreas Beham, Stefan Wagner
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection. CoRR (2013)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Stephan M. Winkler, Gabriel Kronberger
Visualization of genetic lineages and inheritance information in genetic programming. GECCO (Companion) (2013)
Gabriel Kronberger
Declarative Modeling and Bayesian Inference of Dark Matter Halos. EUROCAST (1) (2013)
Gabriel Kronberger, Michael Kommenda, Stefan Wagner, Heinz Dobler
GPDL: a framework-independent problem definition language for grammar-guided genetic programming. GECCO (Companion) (2013)
Stefan Wagner, Gabriel Kronberger
Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education. GECCO (Companion) (2012)
Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller
Macro-Economic Time Series Modeling and Interaction Networks CoRR (2012)
Mathieu d'Aquin, Gabriel Kronberger, Mari Carmen Suárez-Figueroa
Combining Data Mining and Ontology Engineering to Enrich Ontologies and Linked Data. KNOW@LOD (2012)
Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller
Knowledge Discovery through Symbolic Regression with HeuristicLab. ECML/PKDD (2) (2012)
Michael Kommenda, Gabriel Kronberger, Stefan Wagner, Stephan M. Winkler, Michael Affenzeller
On the architecture and implementation of tree-based genetic programming in HeuristicLab. GECCO (Companion) (2012)
Gabriel Kronberger, Stefan Fink, Michael Kommenda, Michael Affenzeller
Macro-economic Time Series Modeling and Interaction Networks. EvoApplications (2) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Gabriel Kronberger