Bogdan Burlacu

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 40

Top Topics

Genetic Programming

Nonlinear Least Squares

Symbolic Regression

Top Venues

GECCO (Companion)

Publications

Bogdan Burlacu
Backend-agnostic Tree Evaluation for Genetic Programming. GECCO Companion (2024)
Etienne Russeil, Fabrício Olivetti de França, Konstantin L. Malanchev, Bogdan Burlacu, Emille E. O. Ishida, Marion Leroux, Clément Michelin, Guillaume Moinard, Emmanuel Gangler
Multi-View Symbolic Regression. CoRR (2024)
Etienne Russeil, Fabrício Olivetti de França, Konstantin L. Malanchev, Bogdan Burlacu, Emille E. O. Ishida, Marion Leroux, Clément Michelin, Guillaume Moinard, Emmanuel Gangler
Multiview Symbolic Regression. GECCO (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)
Bogdan Burlacu
GECCO'2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework. GECCO Companion (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)
Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, M. S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, B. Petersen, Ruben Glatt, T. Nathan Mundhenk, C. S. Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. CoRR (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)
Christian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. GECCO (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)
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)
Bogdan Burlacu
Rank-based Non-dominated Sorting. CoRR (2022)
William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore
Contemporary Symbolic Regression Methods and their Relative Performance. NeurIPS Datasets and Benchmarks (2021)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Effectiveness of Genetic Operations in Symbolic Regression. 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)
William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore
Contemporary Symbolic Regression Methods and their Relative Performance. 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)
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)
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)
Michael Affenzeller, Bogdan Burlacu, Viktoria Dorfer, Sebastian Dorl, Gerhard Halmerbauer, Tilman Königswieser, Michael Kommenda, Julia Vetter, Stephan M. Winkler
White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems. EUROCAST (1) (2019)
Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller
Parsimony measures in multi-objective genetic programming for symbolic regression. GECCO (Companion) (2019)
Mariia Semenkina, Bogdan Burlacu, Michael Affenzeller
Genetic Programming Based Evolvement of Models of Models. 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)
Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller
Cluster Analysis of a Symbolic Regression Search Space. GPTP (2018)
Bogdan Burlacu, Michael Affenzeller
Schema-based diversification in genetic programming. 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)
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)
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)
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)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Effectiveness of Genetic Operations in Symbolic Regression. 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)
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 Affenzeller, Stephan M. Winkler, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
Gaining Deeper Insights in Symbolic Regression. GPTP (2013)
Bogdan Burlacu, Michael Affenzeller, Michael Kommenda
On the Evolutionary Behavior of Genetic Programming with Constants Optimization. EUROCAST (1) (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)
Lavinia Ferariu, Bogdan Burlacu
Multiobjective genetic programming with adaptive clustering. ICCP (2011)
Lavinia Ferariu, Bogdan Burlacu
Multiobjective design of evolutionary hybrid neural networks. ICAC (2011)