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Assessment of multi-objective and coevolutionary genetic programming for predicting the stokes flow around a sphere

Published in 14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control, 2021

Heiner Zille, Fabien Evrard, Julia Reuter, Sanaz Mostaghim, and Berend van Wachem.

Recommended citation: Zille, Heiner, Evrard, Fabien, Reuter, Julia, Mostaghim, Sanaz, and van Wachem, Berend. (2021). Assessment of multi-objective and coevolutionary genetic programming for predicting the stokes flow around a sphere. 14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control, p. 190.
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Genetic programming-based inverse kinematics for robotic manipulators

Published in European Conference on Genetic Programming (Part of EvoStar), 2022

Julia Reuter, Christoph Steup, and Sanaz Mostaghim.

Recommended citation: Reuter, Julia, Steup, Christoph, and Mostaghim, Sanaz. (2022). Genetic programming-based inverse kinematics for robotic manipulators. Genetic Programming: 25th European Conference, EuroGP 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings.
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Towards improving simulations of flows around spherical particles using genetic programming

Published in 2022 IEEE Congress on Evolutionary Computation (CEC), 2022

Julia Reuter, Manoj Cendrollu, Fabien Evrard, Sanaz Mostaghim, and Berend van Wachem.

Recommended citation: Reuter, Julia, Cendrollu, Manoj, Evrard, Fabien, Mostaghim, Sanaz, and van Wachem, Berend. (2022). Towards improving simulations of flows around spherical particles using genetic programming. 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022, pp. 1-8, doi: 10.1109/CEC55065.2022.9870301.
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Graph networks as inductive bias for genetic programming: Symbolic models for particle-laden flows

Published in European Conference on Genetic Programming (Part of EvoStar), 2023

Julia Reuter, Hani Elmestikawy, Fabien Evrard, Sanaz Mostaghim, and Berend van Wachem.

Recommended citation: Reuter, Julia, Elmestikawy, Hani, Evrard, Fabien, Mostaghim, Sanaz, and van Wachem, Berend. (2023). Graph networks as inductive bias for genetic programming: Symbolic models for particle-laden flows. Genetic Programming: 26th European Conference, EuroGP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings
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Multi-objective Island model genetic programming for predicting the stokes flow around a sphere

Published in 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 2023

Julia Reuter, Pravin Pandey, and Sanaz Mostaghim.

Recommended citation: Reuter, Julia, Pandey, Pravin, and Mostaghim, Sanaz. (2023). Multi-objective Island model genetic programming for predicting the stokes flow around a sphere. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexico City, Mexico, 2023, pp. 1485-1490, doi: 10.1109/SSCI52147.2023.10371955.
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Unit-Aware Genetic Programming for the Development of Empirical Equations

Published in International Conference on Parallel Problem Solving from Nature, 2024

Julia Reuter, Viktor Martinek, Roland Herzog, and Sanaz Mostaghim.

Recommended citation: Reuter, Julia, Martinek, Viktor, Herzog, Roland, and Mostaghim, Sanaz. (2024). Unit-Aware Genetic Programming for the Development of Empirical Equations. Parallel Problem Solving from Nature – PPSN XVIII, 168--183.
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Deterministic drag modelling for spherical particles in Stokes regime using data-driven approaches

Published in International Journal of Multiphase Flow, 2024

Hani Elmestikawy, Julia Reuter, Fabien Evrard, Sanaz Mostaghim, and Berend van Wachem.

Recommended citation: Elmestikawy, Hani, Reuter, Julia, Evrard, Fabien, Mostaghim, Sanaz, and van Wachem, Berend. (2024). Deterministic drag modelling for spherical particles in Stokes regime using data-driven approaches. International Journal of Multiphase Flow, 178, 104880.
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The Road to Learning Explainable Inverse Kinematic Models: Graph Neural Networks as Inductive Bias for Symbolic Regression

Published in arXiv, 2025

Pravin Pandey, Julia Reuter, Christoph Steup, and Sanaz Mostaghim.

Recommended citation: Pandey, Pravin, Reuter, Julia, Steup, Christoph, and Mostaghim, Sanaz. (2025). The Road to Learning Explainable Inverse Kinematic Models: Graph Neural Networks as Inductive Bias for Symbolic Regression. arXiv preprint arXiv:2501.13641.
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Development of Symbolic Models Using Genetic Programming and Domain Knowledge

Published in PhD Thesis, 2025

Julia Reuter, Sanaz Mostaghim, Bing Xue, and Leonardo Vanneschi.

Recommended citation: Reuter, Julia, Mostaghim, Sanaz, Xue, Bing, and Vanneschi, Leonardo. (2025). Development of Symbolic Models Using Genetic Programming and Domain Knowledge.
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Drag modelling for flows through assemblies of spherical particles with machine learning: A comparison of approaches

Published in Computers & Fluids, 2026

Julia Reuter, Hani Elmestikawy, Sanaz Mostaghim, and Berend van Wachem.

Recommended citation: Reuter, Julia, Elmestikawy, Hani, Mostaghim, Sanaz, and van Wachem, Berend. (2026). Drag modelling for flows through assemblies of spherical particles with machine learning: A comparison of approaches. Computers & Fluids, 107236.
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Shape Constraints in Symbolic Regression Using Penalized Least Squares

Published in Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2026

Viktor Martinek, Julia Reuter, Ophelia Frotscher, Sanaz Mostaghim, Markus Richter, Roland Herzog.

Recommended citation: Viktor Martinek, Julia Reuter, Ophelia Frotscher, Sanaz Mostaghim, Markus Richter, Roland Herzog. (2026). Shape Constraints in Symbolic Regression Using Penalized Least Squares. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2024. Communications in Computer and Information Science, vol 2559. Springer, Cham. https://doi.org/10.1007/978-3-032-25305-7_16
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Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression

Published in arXiv, 2026

Julia Reuter and Fabricio Olivetti de França.

Recommended citation: Reuter, Julia and de Franca, Fabricio Olivetti. (2026). Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression. arXiv preprint arXiv:2606.06567.
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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Applied Machine Learning

Extension Course (Undergraduate, Graduate, open for the public), UFABC Santo André, 2026

3rd semester, 2026