| Benchmarking AutoML for regression tasks on small tabular data in materials design F Conrad, M Mälzer, M Schwarzenberger, H Wiemer, S Ihlenfeldt Scientific Reports 12 (1), 19350, 2022 | 34 | 2022 |
| Need for UAI–anatomy of the paradigm of usable artificial intelligence for domain-specific AI applicability H Wiemer, D Schneider, V Lang, F Conrad, M Mälzer, E Boos, K Feldhoff, ... Multimodal Technologies and Interaction 7 (3), 27, 2023 | 10 | 2023 |
| Impact of data sampling on performance and robustness of machine learning models in production engineering F Conrad, E Boos, M Mälzer, H Wiemer, S Ihlenfeldt Congress of the German Academic Association for Production Technology, 463-472, 2022 | 3 | 2022 |
| AutoML Applied to Time Series Analysis Tasks in Production Engineering F Conrad, M Mälzer, F Lange, H Wiemer, S Ihlenfeldt Procedia Computer Science 232, 849-860, 2024 | 1 | 2024 |
| Illustration of the Usable AI Paradigm in Production-Engineering Implementation Settings H Wiemer, F Conrad, V Lang, E Boos, M Mälzer, K Feldhoff, L Drowatzky, ... International Conference on Human-Computer Interaction, 640-661, 2023 | 1 | 2023 |
| Leveraging Multi-Task Learning Regressor Chains for Small and Sparse Tabular Data in Materials Design F Conrad, H Wiemer, S Ihlenfeldt Machine Learning: Science and Technology, 2025 | | 2025 |
| Exploring design space: Machine learning for multi-objective materials design optimization with enhanced evaluation strategies F Conrad, JP Stöcker, C Signorini, I de Paula Salgado, H Wiemer, ... Computational Materials Science 246, 113432, 2025 | | 2025 |
| A Metadata Model for Harmonising Engineering Research Data Across Process and Laboratory Boundaries M Zinner, F Conrad, K Feldhoff, H Wiemer, J Weller, S Ihlenfeldt | | |
| Small Dataset Acquisition for Machine Learning Analysis with Possible Uncertainties X Xu, F Conrad, X Xing, O Loeprecht, M Moeckel | | |
