Please also refer to my Google Scholar Profile for a full list of publications.
I Prefer not to Say: Operationalizing Fair and User-guided Data Minimization
Tobias Leemann, Martin Pawelczyk, Christian Thomas Eberle, and Gjergji Kasneci. 2022.
Disentangling Visual Embeddings with Minimal Distributional Assumptions
Tobias Leemann,* Michael Kirchhof,* Yao Rong, and Gjergji Kasneci. 2022.
Deep Neural Networks and Tabular Data: A Survey
Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, and Gjergji Kasneci. IEEE Transactions on Neural Networks and Learning Systems, Early Access, 2022.
A Consistent and Efficient Evaluation Strategy for Attribution Methods
Yao Rong,* Tobias Leemann,* Vadim Borisov, Gjergji Kasneci, and Enkelejda Kasneci. International Conference on Machine Learning, 2022.
Multi-Step Training for Predicting Roundabout Traffic Situations
Moritz Sackmann, Tobias Leemann, Henrik Bey, Ulrich Hofmann, and Jörn Thielecke. IEEE International Intelligent Transportation Systems Conference (ITSC), 2021.
Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling
Tobias Leemann, Moritz Sackmann, Jörn Thielecke, and Ulrich Hofmann. 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2021.
