| Harnessing Prior Knowledge for Explainable Machine Learning: An Overview K Beckh, S Müller, M Jakobs, V Toborek, H Tan, R Fischer, P Welke, ... First IEEE Conference on Secure and Trustworthy Machine Learning, 2023 | 81* | 2023 |
| A Unified Framework for Assessing Energy Efficiency of Machine Learning R Fischer, M Jakobs, S Mücke, K Morik Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 32 | 2022 |
| Yes We Care! - Certification for Machine Learning Methods Through the Care Label Framework K Morik, H Kotthaus, R Fischer, S Mücke, M Jakobs, N Piatkowski, A Pauly, ... Frontiers in Artificial Intelligence, 2022 | 21* | 2022 |
| Solving Abstract Reasoning Tasks with Grammatical Evolution R Fischer, M Jakobs, S Mücke, K Morik LWDA, 6-10, 2020 | 19 | 2020 |
| AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting R Fischer, A Saadallah Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 18 | 2024 |
| Towards More Sustainable and Trustworthy Reporting in Machine Learning R Fischer, T Liebig, K Morik Data Mining and Knowledge Discovery, 1-20, 2024 | 15 | 2024 |
| The Care Label Concept: A Certification Suite for Trustworthy and Resource-aware Machine Learning K Morik, H Kotthaus, L Heppe, D Heinrich, R Fischer, A Pauly, ... arXiv preprint arXiv:2106.00512, 2021 | 13 | 2021 |
| No Cloud on the Horizon: Probabilistic Gap Filling in Satellite Image Series R Fischer, N Piatkowski, C Pelletier, GI Webb, F Petitjean, K Morik 2020 IEEE 7th International Conference on Data Science and Advanced …, 2020 | 10 | 2020 |
| Prioritization of Identified Data Science Use Cases in Industrial Manufacturing via C-EDIF Scoring R Fischer, A Pauly, R Wilking, A Kini, D Graurock 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | 8 | 2023 |
| MetaQuRe: Meta-learning from Model Quality and Resource Consumption R Fischer, M Wever, S Buschjäger, T Liebig Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 5 | 2024 |
| Energy Efficiency Considerations for Popular AI Benchmarks R Fischer, M Jakobs, K Morik AI for Energy Innovation Workshop at 37th AAAI Conference on Artificial …, 2023 | 5 | 2023 |
| Bridging the Communication Gap: Evaluating AI Labeling Practices for Trustworthy AI Development R Fischer, M Wischnewski, A van der Staay, K Poitz, C Janiesch, T Liebig AAAI/ACM Conference on AI, Ethics, and Society 8 (1), 926-939, 2025 | 4 | 2025 |
| Stress-Testing USB Accelerators for Efficient Edge Inference A Van Der Staay, R Fischer, S Buschjäger 2024 IEEE/ACM Symposium on Edge Computing (SEC), 1-14, 2024 | 4* | 2024 |
| Ground-Truthing AI Energy Consumption: Validating CodeCarbon Against External Measurements R Fischer arXiv preprint arXiv:2509.22092, 2025 | 2 | 2025 |
| Advancing the Sustainability of Machine Learning and Artificial Intelligence via Labeling and Meta-Learning R Fischer PhD Thesis - TU Dortmund University, 2025 | 2 | 2025 |
| Reflective Design Theorizing with User Interviews: A Case Study for AI Energy Labels A van der Staay, R Fischer, M Wischnewski, K Poitz, C Janiesch International Conference on Design Science Research in Information Systems …, 2025 | 1 | 2025 |
| Improving Trust in AI Through Sustainable and Trustworthy Reporting R Fischer, M Bunse DataNinja sAIOnARA Conference, 2024 | 1 | 2024 |
| Parameter Sharing for Spatio-Temporal Process Models. R Fischer, N Piatkowski, K Morik LWDA, 89-93, 2019 | 1 | 2019 |
| Benefits and Limitations of Using GenAI for Political Education and Municipal Elections R Fischer, Y Abdelrahim, K Poitz arXiv preprint arXiv:2510.11749, 2025 | | 2025 |
| Lift What You Can: Green Online Learning with Heterogeneous Ensembles K Köbschall, S Buschjäger, R Fischer, L Hartung, S Kramer arXiv preprint arXiv:2509.18962, 2025 | | 2025 |
Matthias JakobsResearch Associate, TU DortmundVerified email at tu-dortmund.de
