| Bias in data‐driven artificial intelligence systemsAn introductory survey E Ntoutsi, P Fafalios, U Gadiraju, V Iosifidis, W Nejdl, ME Vidal, S Ruggieri, ... Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (3
, 2020 | 897 | 2020 |
| Learning model-agnostic counterfactual explanations for tabular data M Pawelczyk, K Broelemann, G Kasneci Proceedings of the web conference 2020, 3126-3132, 2020 | 241 | 2020 |
| On counterfactual explanations under predictive multiplicity M Pawelczyk, K Broelemann, G Kasneci Conference on Uncertainty in Artificial Intelligence, 809-818, 2020 | 92 | 2020 |
| SketchMapia: Qualitative representations for the alignment of sketch and metric maps A Schwering, J Wang, M Chipofya, S Jan, R Li, K Broelemann Spatial cognition & computation 14 (3), 220-254, 2014 | 81 | 2014 |
| Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth E Kasneci, T Kübler, K Broelemann, G Kasneci Computers in Human Behavior 68, 450-455, 2017 | 25 | 2017 |
| DeepTLF: robust deep neural networks for heterogeneous tabular data V Borisov, K Broelemann, E Kasneci, G Kasneci International Journal of Data Science and Analytics 16 (1), 85-100, 2023 | 23 | 2023 |
| A gradient-based split criterion for highly accurate and transparent model trees K Broelemann, G Kasneci arXiv preprint arXiv:1809.09703, 2018 | 18 | 2018 |
| Automatic understanding of sketch maps using context-aware classification K Broelemann, X Jiang, A Schwering Expert systems with applications 45, 195-207, 2016 | 15 | 2016 |
| Leveraging model inherent variable importance for stable online feature selection J Haug, M Pawelczyk, K Broelemann, G Kasneci Proceedings of the 26th ACM SIGKDD International Conference on Knowledge
, 2020 | 14 | 2020 |
| Bias in data-driven artificial intelligence systemsan introductory survey. WIREs Data Min Knowl Discov 10 (3): e1356 E Ntoutsi, P Fafalios, U Gadiraju, V Iosifidis, W Nejdl, ME Vidal, S Ruggieri, ... | 13 | 2020 |
| Hierarchical graph representation for symbol spotting in graphical document images K Broelemann, A Dutta, X Jiang, J Lladós Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR
, 2012 | 13 | 2012 |
| A System for Automatic Localization and Recognition of Sketch Map Objects. K Broelemann Understanding and Processing Sketch Maps@ COSIT, 11-20, 2011 | 11 | 2011 |
| LTD-RBM: Robust and fast latent truth discovery using restricted Boltzmann machines K Broelemann, T Gottron, G Kasneci 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 143-146, 2017 | 10 | 2017 |
| Hierarchical plausibility-graphs for symbol spotting in graphical documents K Broelemann, A Dutta, X Jiang, J Lladós International Workshop on Graphics Recognition, 25-37, 2013 | 10 | 2013 |
| Automatic street graph construction in sketch maps K Broelemann, X Jiang, A Schwering International workshop on graph-based representations in pattern recognition
, 2011 | 10 | 2011 |
| Interventional SHAP values and interaction values for piecewise linear regression trees A Zern, K Broelemann, G Kasneci Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11164
, 2023 | 8 | 2023 |
| Dynamic model tree for interpretable data stream learning J Haug, K Broelemann, G Kasneci 2022 IEEE 38th International Conference on Data Engineering (ICDE), 2562-2574, 2022 | 8 | 2022 |
| Restricted boltzmann machines for robust and fast latent truth discovery K Broelemann, T Gottron, G Kasneci arXiv preprint arXiv:1801.00283, 2017 | 8 | 2017 |
| A region-based method for sketch map segmentation K Broelemann, X Jiang Graphics Recognition. New Trends and Challenges: 9th International Workshop
, 2013 | 8 | 2013 |
| Graph-based markerless registration of city maps using geometric hashing X Jiang, K Broelemann, S Wachenfeld, A Krüger Computer Vision and Image Understanding 115 (7), 1032-1043, 2011 | 8 | 2011 |
