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Martin Pawelczyk
Martin Pawelczyk
Postdoc, Harvard University
Verified email at uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
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
6122021
Learning model-agnostic counterfactual explanations for tabular data
M Pawelczyk, K Broelemann, G Kasneci
Proceedings of The Web Conference (WWW) 2020, 3126-3132, 2020
2122020
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
1292022
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
1162023
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
792020
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
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
In-context unlearning: Language models as few shot unlearners
M Pawelczyk, S Neel, H Lakkaraju
International Conference on Machine Learning (ICML) 2024, 2024
462024
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
422022
Linking Aid to the Sustainable Development Goals–a machine learning approach
A Pincet, S Okabe, M Pawelczyk
OECD, 2019
312019
On the Privacy Risks of Algorithmic Recourse
M Pawelczyk, H Lakkaraju, S Neel
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2023
202023
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
152023
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
142020
Gaussian Membership Inference Privacy
T Leemann*, M Pawelczyk*, G Kasneci
Proceedings of the Neural Information Processing Systems (NeurIPS) 2023, 2023
72023
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
2*2024
Decomposing Counterfactual Explanations for Consequential Decision Making
M Pawelczyk, L Tiyavorabun, G Kasneci
Workshop on Socially Responsible Machine Learning (SRML), ICLR 2022, 2022
12022
Towards Non-adversarial Algorithmic Recourse
T Leemann, M Pawelczyk, B Prenkaj, G Kasneci
World Conference on Explainable Artificial Intelligence, 395-419, 2024
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
2024
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