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Alexander Hagg
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Cited by
Year
Fine-Tuning Property Domain Weighting Factors and the Objective Function in Force Field Parameter Optimization
R Strickstrock, A Hagg, M Hülsmann, K Kirschner, D Reith
2024
Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-Optimization
A Hagg, ML Kliemank, A Asteroth, D Wilde, MC Bedrunka, H Foysi, ...
Evolutionary Computation 31 (3), 287-307, 2023
12023
Open-source machine learning in computational chemistry
A Hagg, KN Kirschner
Journal of Chemical Information and Modeling 63 (15), 4505-4532, 2023
142023
On the Suitability of Representations for Quality Diversity Optimization of Shapes
L Scarton, A Hagg
Proceedings of the Genetic and Evolutionary Computation Conference, 963-971, 2023
2023
Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization
M Müller, A Hagg, R Strickstrock, M Hülsmann, A Asteroth, ...
Journal of Chemical Information and Modeling 63 (7), 1872-1881, 2023
12023
Artificial intelligence in elite sports—a narrative review of success stories and challenges
F Hammes, A Hagg, A Asteroth, D Link
Frontiers in Sports and Active Living 4, 861466, 2022
312022
Künstliche Intelligenz für den Spitzensport im Spannungsfeld zwischen Big und Small Data
A Hagg, A Asteroth, C Rasche, K Bach, M Pfeiffer
32022
Discovering the preference hypervolume: an interactive model for real world computational co-creativity
A Hagg
Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden …, 2021
12021
Expressivity of parameterized and data-driven representations in quality diversity search
A Hagg, S Berns, A Asteroth, S Colton, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 678-686, 2021
162021
Phenotypic niching using quality diversity algorithms
A Hagg
Metaheuristics for Finding Multiple Solutions, 287-315, 2021
42021
Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im inter-nationalen Spitzensport–zwischen Small und Big Data
A Hagg, A Asteroth, M Pfeiffer, F Hammes, D Link
spinfortec 2020 digital, 26, 2020
2020
Einsatz von Künstlicher Intelligenz im internationalen Spitzensport–Eine Erhebung des Status Quo
F Hammes, D Link, M Lames, A Hagg, A Asteroth, M Pfeiffer
spinfortec 2020 digital, 28, 2020
2020
An analysis of phenotypic diversity in multi-solution optimization
A Hagg, M Preuss, A Asteroth, T Bäck
International Conference on Bioinspired Methods and Their Applications, 43-55, 2020
82020
A Deep Dive Into Exploring the Preference Hypervolume
A Hagg, A Asteroth, T Bäck
International Conference on Computational Creativity, 394-397, 2020
22020
Designing air flow with surrogate-assisted phenotypic niching
A Hagg, D Wilde, A Asteroth, T Bäck
International Conference on Parallel Problem Solving from Nature, 140-153, 2020
202020
AErOmAt Abschlussbericht
A Asteroth
Deutsche Nationalbibliothek, 2020
2020
Prediction of neural network performance by phenotypic modeling
A Hagg, M Zaefferer, J Stork, A Gaier
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
72019
Modeling user selection in quality diversity
A Hagg, A Asteroth, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 116-124, 2019
82019
Prototype discovery using quality-diversity
A Hagg, A Asteroth, T Bäck
Parallel Problem Solving from Nature–PPSN XV: 15th International Conference …, 2018
312018
Multi-stage evolution of single-and multi-objective MCLP: Successive placement of charging stations
H Spieker, A Hagg, A Gaier, S Meilinger, A Asteroth
Soft Computing 21, 4859-4872, 2017
142017
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