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 | 44* | 2023 |
Explainable online deep neural network selection using adaptive saliency maps for time series forecasting A Saadallah, M Jakobs, K Morik Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 19 | 2021 |
Towards complex adaptive control systems in intralogistics T Kirks, J Jost, T Uhlott, M Jakobs The 21st IEEE International Conference on Intelligent Transportation Systems, 2018 | 16* | 2018 |
Yes we care!-certification for machine learning methods through the care label framework KJ Morik, H Kotthaus, R Fischer, S Mücke, M Jakobs, N Piatkowski, ... Frontiers in Artificial Intelligence 5, 975029, 2022 | 13* | 2022 |
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 | 13 | 2022 |
Explainable online ensemble of deep neural network pruning for time series forecasting A Saadallah, M Jakobs, K Morik Machine Learning 111 (9), 3459-3487, 2022 | 11 | 2022 |
Solving Abstract Reasoning Tasks with Grammatical Evolution R Fischer, M Jakobs, S Mücke, K Morik Lernen, Wissen, Daten, Analysen, 6 - 10, 2020 | 11 | 2020 |
Evaluation of the application of smart glasses for decentralized control systems in logistics T Kirks, J Jost, T Uhlott, J Püth, M Jakobs 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 4470-4476, 2019 | 9 | 2019 |
Explaining quantum circuits with shapley values: Towards explainable quantum machine learning R Heese, T Gerlach, S Mücke, S Müller, M Jakobs, N Piatkowski arXiv preprint arXiv:2301.09138, 2023 | 7 | 2023 |
Fooling perturbation-based explainability methods R Wilking, M Jakobs, K Morik Workshop on Trustworthy Artificial Intelligence as a part of the ECML/PKDD …, 2022 | 4 | 2022 |
An empirical evaluation of the Rashomon effect in explainable machine learning S Müller, V Toborek, K Beckh, M Jakobs, C Bauckhage, P Welke Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 3 | 2023 |
Energy efficiency considerations for popular ai benchmarks R Fischer, M Jakobs, K Morik arXiv preprint arXiv:2304.08359, 2023 | 3 | 2023 |
Shapley Values with Uncertain Value Functions R Heese, S Mücke, M Jakobs, T Gerlach, N Piatkowski International Symposium on Intelligent Data Analysis, 156-168, 2023 | 1 | 2023 |
SancScreen: Towards a Real-world Dataset for Evaluating Explainability Methods. M Jakobs, H Kotthaus, I Röder, M Baritz LWDA, 33-44, 2022 | 1 | 2022 |
Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting M Jakobs, A Saadallah 2023 IEEE International Conference on Data Mining (ICDM), 180-189, 2023 | | 2023 |
Online Deep Hybrid Ensemble Learning for Time Series Forecasting A Saadallah, M Jakobs Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | | 2023 |