| Explanations for neural networks by neural networks S Marton, S Lüdtke, C Bartelt Applied Sciences 12 (3), 980, 2022 | 17* | 2022 |
| GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent S Marton, S Lüdtke, C Bartelt, H Stuckenschmidt Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 14323 …, 2024 | 8* | 2024 |
| GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data S Marton, S Lüdtke, C Bartelt, H Stuckenschmidt International Conference on Learning Representations, 2024 | 6* | 2024 |
| Bias mitigation for large language models using adversarial learning JS Ernst, S Marton, J Brinkmann, E Vellasques, D Foucard, M Kraemer, ... CEUR Workshop Proceedings 3523, 1-14, 2023 | 4 | 2023 |
| Mapping glacier basal sliding applying machine learning J Umlauft, CW Johnson, P Roux, DT Trugman, A Lecointre, A Walpersdorf, ... Journal of Geophysical Research: Earth Surface 128 (11), e2023JF007280, 2023 | 3 | 2023 |
| Explaining Neural Networks without Access to Training Data S Marton, S Lüdtke, C Bartelt, A Tschalzev, H Stuckenschmidt Machine Learning, 2024 | 2 | 2024 |
| DSEG-LIME--Improving Image Explanation by Hierarchical Data-Driven Segmentation P Knab, S Marton, C Bartelt arXiv preprint arXiv:2403.07733, 2024 | 1 | 2024 |
| Interpreting Outliers in Time Series Data through Decoding Autoencoder P Knab, S Marton, C Bartelt, R Fuder arXiv preprint arXiv:2409.01713, 2024 | | 2024 |
| SYMPOL: Symbolic Tree-Based On-Policy Reinforcement Learning S Marton, T Grams, F Vogt, S Lüdtke, C Bartelt, H Stuckenschmidt arXiv preprint arXiv:2408.08761, 2024 | | 2024 |
| A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data A Tschalzev, S Marton, S Lüdtke, C Bartelt, H Stuckenschmidt arXiv preprint arXiv:2407.02112, 2024 | | 2024 |
| Machine learning for converting Black-Box models to interpretable functions S Marton, C Bartelt, H Stuckenschmidt | | 2020 |
Christian BarteltUniversity of Mannheim在 uni-mannheim.de 的电子邮件经过验证
