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Dive into the research topics where Lukas Kammerer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Projects
- 2 Finished
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Josef Ressel Zentrum für Symbolische Regression
Kronberger, G. (PI), Beneder, M. (CoI), Burlacu, B. (CoI), Haider, C. A. (CoI), Kammerer, L. (CoI), Bachinger, F. (CoI) & Jödicke, D. (CoI)
01.01.2018 → 31.12.2022
Project: Research Project
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EREMA Recycling 4.0
Kronberger, G. (PI) & Kammerer, L. (CoI)
01.04.2017 → 31.12.2019
Project: Research Project
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A precise symbolic emulator of the linear matter power spectrum
Bartlett, D. J., Kammerer, L., Kronberger, G., Desmond, H., Ferreira, P. G., Wandelt, B. D., Burlacu, B., Alonso, D. & Zennaro, M., 1 Jun 2024, In: Astronomy and Astrophysics. 686, A209.Research output: Contribution to journal › Article › peer-review
Open Access4 Citations (Scopus) -
Bias and Variance Analysis of Contemporary Symbolic Regression Methods
Kammerer, L., Kronberger, G. & Winkler, S., 28 Nov 2024, In: Applied Sciences. 14, 23, 11061.Research output: Contribution to journal › Article › peer-review
Open Access -
The Inefficiency of Genetic Programming for Symbolic Regression
Kronberger, G., Olivetti de Franca, F., Desmond, H., Bartlett, D. J. & Kammerer, L., Sept 2024, Parallel Problem Solving from Nature – PPSN XVIII - 18th International Conference, PPSN 2024, Proceedings. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.). Springer, p. 273-289 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15148 LNCS).Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review
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Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization.
Kammerer, L., Kronberger, G. & Kommenda, M., 2022, p. 139-146. 8 p.Research output: Contribution to conference › Paper › peer-review
1 Citation (Scopus) -
Empirical analysis of variance for genetic programming based symbolic regression
Kammerer, L., Kronberger, G. & Winkler, S., 7 Jul 2021, GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, p. 251-252 2 p. (GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion).Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review
Open Access2 Citations (Scopus)