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pro vyhledávání: '"WINKLER, Stephan"'
Symbolic regression is a machine learning method with the goal to produce interpretable results. Unlike other machine learning methods such as, e.g. random forests or neural networks, which are opaque, symbolic regression aims to model and map data i
Externí odkaz:
http://arxiv.org/abs/2406.03585
Autor:
Haghofer, Andreas, Parlak, Eda, Bartel, Alexander, Donovan, Taryn A., Assenmacher, Charles-Antoine, Bolfa, Pompei, Dark, Michael J., Fuchs-Baumgartinger, Andrea, Klang, Andrea, Jäger, Kathrin, Klopfleisch, Robert, Merz, Sophie, Richter, Barbara, Schulman, F. Yvonne, Janout, Hannah, Ganz, Jonathan, Scharinger, Josef, Aubreville, Marc, Winkler, Stephan M., Kiupel, Matti, Bertram, Christof A.
Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibil
Externí odkaz:
http://arxiv.org/abs/2309.15031
Vectorial Genetic Programming (Vec-GP) extends GP by allowing vectors as input features along regular, scalar features, using them by applying arithmetic operations component-wise or aggregating vectors into scalars by some aggregation function. Vec-
Externí odkaz:
http://arxiv.org/abs/2303.03200
Publikováno v:
In: Moreno-Diaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory EUROCAST 2022. Lecture Notes in Computer Science, vol 13789
Describing dynamic medical systems using machine learning is a challenging topic with a wide range of applications. In this work, the possibility of modeling the blood glucose level of diabetic patients purely on the basis of measured data is describ
Externí odkaz:
http://arxiv.org/abs/2209.13852
Autor:
Burlacu, Bogdan, Kommenda, Michael, Kronberger, Gabriel, Winkler, Stephan, Affenzeller, Michael
Particle-based modeling of materials at atomic scale plays an important role in the development of new materials and understanding of their properties. The accuracy of particle simulations is determined by interatomic potentials, which allow to calcu
Externí odkaz:
http://arxiv.org/abs/2206.06422
Autor:
Kronberger, Gabriel, Kammerer, Lukas, Burlacu, Bogdan, Winkler, Stephan M., Kommenda, Michael, Affenzeller, Michael
Publikováno v:
eIn: Banzhaf W. et al (eds) Genetic Programming Theory and Practice XVI. Genetic and Evolutionary Computation. Springer, Cham. pp 85-102 (2019)
In this chapter we take a closer look at the distribution of symbolic regression models generated by genetic programming in the search space. The motivation for this work is to improve the search for well-fitting symbolic regression models by using i
Externí odkaz:
http://arxiv.org/abs/2109.13898
Autor:
Kammerer, Lukas, Kronberger, Gabriel, Burlacu, Bogdan, Winkler, Stephan M., Kommenda, Michael, Affenzeller, Michael
Publikováno v:
In: Banzhaf W. et al (eds) Genetic Programming Theory and Practice XVII, pp 79-99 (2020)
Symbolic regression is a powerful system identification technique in industrial scenarios where no prior knowledge on model structure is available. Such scenarios often require specific model properties such as interpretability, robustness, trustwort
Externí odkaz:
http://arxiv.org/abs/2109.13895
Akademický článek
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Akademický článek
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Autor:
Vivo-Vilches, Carlos, Rugel, Georg, Lachner, Johannes, Koll, Dominik, Stübner, Konstanze, Fichter, Sebastian, Winkler, Stephan, Wallner, Anton
Publikováno v:
In Nuclear Inst. and Methods in Physics Research, B July 2023 540:188-193
