Multiobjective genetic programming with adaptive clustering. - Lavinia Ferariu; Bogdan Burlacu (ICCP, 2011)

Multiobjective design of evolutionary hybrid neural networks. - Lavinia Ferariu; Bogdan Burlacu (ICAC, 2011)

On the Evolutionary Behavior of Genetic Programming with Constants Optimization. - Bogdan Burlacu; Michael Affenzeller; 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)

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

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)

On the Effectiveness of Genetic Operations in Symbolic Regression. - Bogdan Burlacu; Michael Affenzeller; Michael Kommenda (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)

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)

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)

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)

Schema-based diversification in genetic programming. - Bogdan Burlacu; Michael Affenzeller (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)

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

White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems. - Michael Affenzeller; Bogdan Burlacu; Viktoria Dorfer; Sebastian Dorl; Gerhard Halmerbauer; Tilman Königswieser; Michael Kommenda; Julia Vetter; Stephan M. Winkler (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)

Genetic Programming Based Evolvement of Models of Models. - Mariia Semenkina; Bogdan Burlacu; 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)

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)

Contemporary Symbolic Regression Methods and their Relative Performance. - William G. La Cava; Patryk Orzechowski; Bogdan Burlacu; Fabrício Olivetti de França; Marco Virgolin; Ying Jin; Michael Kommenda; Jason H. Moore (NeurIPS Datasets and Benchmarks, 2021)

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

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)

Rank-based Non-dominated Sorting. - Bogdan Burlacu (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)

GECCO'2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework. - Bogdan Burlacu (GECCO Companion, 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)

Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. - Fabrício Olivetti de França; Marco Virgolin; Michael Kommenda; Maimuna S. Majumder; Miles D. Cranmer; Guilherme Espada; Leon Ingelse; Alcides Fonseca; Mikel Landajuela; Brenden K. Petersen; Ruben Glatt; T. Nathan Mundhenk; et al. (CoRR, 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)

Backend-agnostic Tree Evaluation for Genetic Programming. - Bogdan Burlacu (GECCO Companion, 2024)

Multiview Symbolic Regression. - Etienne Russeil; Fabrício Olivetti de França; Konstantin L. Malanchev; Bogdan Burlacu; Emille E. O. Ishida; Marion Leroux; Clément Michelin; Guillaume Moinard; Emmanuel Gangler (GECCO, 2024)

Enhancing the Computational Efficiency of Genetic Programming Through Alternative Floating-Point Primitives. - Christopher Crary; Bogdan Burlacu; Wolfgang Banzhaf (PPSN (1), 2024)

Multi-View Symbolic Regression. - Etienne Russeil; Fabrício Olivetti de França; Konstantin L. Malanchev; Bogdan Burlacu; Emille E. O. Ishida; Marion Leroux; Clément Michelin; Guillaume Moinard; Emmanuel Gangler (CoRR, 2024)

Population diversity and inheritance in genetic programming for symbolic regression. - Bogdan Burlacu; Kaifeng Yang; Michael Affenzeller (Nat. Comput., 2024)

Call for Action: towards the next generation of symbolic regression benchmark. - Guilherme Seidyo Imai Aldeia; Hengzhe Zhang; Geoffrey F. Bomarito; Miles D. Cranmer; Alcides Fonseca; Bogdan Burlacu; William G. La Cava; Fabrício Olivetti de França (CoRR, 2025)

Using FPGA devices to accelerate the evaluation phase of tree-based genetic programming: an extended analysis. - Christopher Crary; Wesley Piard; Greg Stitt; Benjamin M. Hicks; Caleb Bean; Bogdan Burlacu; Wolfgang Banzhaf (Genet. Program. Evolvable Mach., 2025)

Zobrist Hash-based Duplicate Detection in Symbolic Regression. - Bogdan Burlacu (CoRR, 2025)

SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation. - Fabrício Olivetti de França; Marco Virgolin; Michael Kommenda; Maimuna S. Majumder; Miles D. Cranmer; Guilherme Espada; Leon Ingelse; Alcides Fonseca; Mikel Landajuela; Brenden K. Petersen; Ruben Glatt; T. Nathan Mundhenk; et al. (IEEE Trans. Evol. Comput., 2025)