| Deep neural networks and tabular data: A survey V Borisov, T Leemann, K Seßler, J Haug, M Pawelczyk, G Kasneci IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 | 659 | 2021 |
| Learning model-agnostic counterfactual explanations for tabular data M Pawelczyk, K Broelemann, G Kasneci Proceedings of The Web Conference (WWW) 2020, 3126-3132, 2020 | 219 | 2020 |
| OpenXAI: Towards a Transparent Evaluation of Model Explanations C Agarwal, E Saxena, S Krishna, M Pawelczyk, N Johnson, I Puri, M Zitnik, ... Proceedings of the Neural Information Processing Systems (NeurIPS) 2022 …, 2022 | 136 | 2022 |
| Language models are realistic tabular data generators V Borisov, K Seßler, T Leemann, M Pawelczyk, G Kasneci 11th International Conference on Learning Representations (ICLR) 2023, 2023 | 134 | 2023 |
| Carla: a python library to benchmark algorithmic recourse and counterfactual explanation algorithms M Pawelczyk, S Bielawski, J Heuvel, T Richter, G Kasneci Proceedings of the Neural Information Processing Systems (NeurIPS) 2021 …, 2021 | 93* | 2021 |
| On counterfactual explanations under predictive multiplicity M Pawelczyk, K Broelemann, G Kasneci Conference on Uncertainty in Artificial Intelligence (UAI), 809-818, 2020 | 83 | 2020 |
| Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis M Pawelczyk, C Agarwal, S Joshi, S Upadhyay, H Lakkaraju International Conference on Artificial Intelligence and Statistics (AISTATS …, 2022 | 68* | 2022 |
| In-context unlearning: Language models as few shot unlearners M Pawelczyk, S Neel, H Lakkaraju International Conference on Machine Learning (ICML) 2024, 2024 | 50 | 2024 |
| Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse M Pawelczyk, T Datta, J van-den-Heuvel, G Kasneci, H Lakkaraju 11th International Conference on Learning Representations (ICLR) 2023, 2023 | 48* | 2023 |
| Rethinking stability for attribution-based explanations C Agarwal, N Johnson, M Pawelczyk, S Krishna, E Saxena, M Zitnik, ... ICLR 2022 Workshop on PAIR^2Struct: Privacy, Accountability …, 2022 | 47 | 2022 |
| Linking Aid to the Sustainable Development Goals–a machine learning approach A Pincet, S Okabe, M Pawelczyk OECD, 2019 | 31 | 2019 |
| On the Privacy Risks of Algorithmic Recourse M Pawelczyk, H Lakkaraju, S Neel International Conference on Artificial Intelligence and Statistics (AISTATS …, 2023 | 21 | 2023 |
| On the Trade-Off between Actionable Explanations and the Right to be Forgotten M Pawelczyk, T Leemann, A Biega, G Kasneci 11th International Conference on Learning Representations (ICLR) 2023, 2023 | 16 | 2023 |
| Leveraging model inherent variable importance for stable online feature selection J Haug, M Pawelczyk, K Broelemann, G Kasneci 26th ACM SIGKDD International Conference on Knowledge Discovery & Data …, 2020 | 14 | 2020 |
| Gaussian Membership Inference Privacy T Leemann*, M Pawelczyk*, G Kasneci Proceedings of the Neural Information Processing Systems (NeurIPS) 2023, 2023 | 9 | 2023 |
| Model selection in local approximation gaussian processes: A markov random fields approach H Jalali, M Pawelczyk, G Kasneci 2021 IEEE International Conference on Big Data (Big Data), 768-778, 2021 | 5* | 2021 |
| I Prefer Not To Say: Protecting User Consent in Models with Optional Personal Data T Leemann, M Pawelczyk, CT Eberle, G Kasneci Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21312 …, 2024 | 3* | 2024 |
| Machine Unlearning Fails to Remove Data Poisoning Attacks M Pawelczyk, JZ Di, Y Lu, G Kamath, A Sekhari, S Neel arXiv preprint arXiv:2406.17216, 2024 | 1 | 2024 |
| Decomposing Counterfactual Explanations for Consequential Decision Making M Pawelczyk, L Tiyavorabun, G Kasneci Workshop on Socially Responsible Machine Learning (SRML), ICLR 2022, 2022 | 1 | 2022 |
| Towards Non-adversarial Algorithmic Recourse T Leemann, M Pawelczyk, B Prenkaj, G Kasneci World Conference on Explainable Artificial Intelligence, 395-419, 2024 | | 2024 |
Gjergji KasneciProfessor at the Technical University of Munich在 tum.de 的电子邮件经过验证
