Tobias Leemann

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 23

Top Topics

Distributional Assumptions

Multiple Hypotheses

Additive Models

Top Venues

Publications

Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, Gjergji Kasneci
Deep Neural Networks and Tabular Data: A Survey. IEEE Trans. Neural Networks Learn. Syst. 35 (6) (2024)
Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci
Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals. KDD (2024)
Tobias Leemann, Martin Pawelczyk, Bardh Prenkaj, Gjergji Kasneci
Towards Non-Adversarial Algorithmic Recourse. CoRR (2024)
Tobias Leemann, Martin Pawelczyk, Christian Thomas Eberle, Gjergji Kasneci
I Prefer Not to Say: Protecting User Consent in Models with Optional Personal Data. AAAI (2024)
Yao Rong, Tobias Leemann, Thai-trang Nguyen, Lisa Fiedler, Peizhu Qian, Vaibhav V. Unhelkar, Tina Seidel, Gjergji Kasneci, Enkelejda Kasneci
Towards Human-Centered Explainable AI: A Survey of User Studies for Model Explanations. IEEE Trans. Pattern Anal. Mach. Intell. 46 (4) (2024)
Tobias Leemann, Alina Fastowski, Felix Pfeiffer, Gjergji Kasneci
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers. CoRR (2024)
Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes. CoRR (2023)
Martin Pawelczyk, Tobias Leemann, Asia Biega, Gjergji Kasneci
On the Trade-Off between Actionable Explanations and the Right to be Forgotten. ICLR (2023)
Vadim Borisov, Kathrin Seßler, Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci
Language Models are Realistic Tabular Data Generators. ICLR (2023)
Tobias Leemann, Michael Kirchhof, Yao Rong, Enkelejda Kasneci, Gjergji Kasneci
When are post-hoc conceptual explanations identifiable? UAI (2023)
Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci
Gaussian Membership Inference Privacy. CoRR (2023)
Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci
Gaussian Membership Inference Privacy. NeurIPS (2023)
Tobias Leemann, Michael Kirchhof, Yao Rong, Enkelejda Kasneci, Gjergji Kasneci
Disentangling Embedding Spaces with Minimal Distributional Assumptions. CoRR (2022)
Yao Rong, Tobias Leemann, Vadim Borisov, Gjergji Kasneci, Enkelejda Kasneci
Evaluating Feature Attribution: An Information-Theoretic Perspective. CoRR (2022)
Martin Pawelczyk, Tobias Leemann, Asia Biega, Gjergji Kasneci
On the Trade-Off between Actionable Explanations and the Right to be Forgotten. CoRR (2022)
Vadim Borisov, Kathrin Seßler, Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci
Language Models are Realistic Tabular Data Generators. CoRR (2022)
Yao Rong, Tobias Leemann, Thai-trang Nguyen, Lisa Fiedler, Tina Seidel, Gjergji Kasneci, Enkelejda Kasneci
Towards Human-centered Explainable AI: User Studies for Model Explanations. CoRR (2022)
Yao Rong, Tobias Leemann, Vadim Borisov, Gjergji Kasneci, Enkelejda Kasneci
A Consistent and Efficient Evaluation Strategy for Attribution Methods. ICML (2022)
Tobias Leemann, Martin Pawelczyk, Christian Thomas Eberle, Gjergji Kasneci
I Prefer not to Say: Operationalizing Fair and User-guided Data Minimization. CoRR (2022)
Tobias Leemann, Moritz Sackmann, Jörn Thielecke, Ulrich Hofmann
Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling. CoRR (2021)
Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, Gjergji Kasneci
Deep Neural Networks and Tabular Data: A Survey. CoRR (2021)
Moritz Sackmann, Tobias Leemann, Henrik Bey, Ulrich Hofmann, Jörn Thielecke
Multi-Step Training for Predicting Roundabout Traffic Situations. ITSC (2021)
Tobias Leemann, Moritz Sackmann, Jörn Thielecke, Ulrich Hofmann
Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling. ESANN (2021)