| Gan-leaks: A taxonomy of membership inference attacks against gans D Chen, N Yu, Y Zhang, M Fritz The ACM Conference on Computer and Communications Security (CCS) 2020, 2019 | 336* | 2019 |
| Badnl: Backdoor attacks against nlp models with semantic-preserving improvements X Chen, A Salem, D Chen, M Backes, S Ma, Q Shen, Z Wu, Y Zhang Proceedings of the 37th Annual Computer Security Applications Conference …, 2021 | 287 | 2021 |
| Gs-wgan: A gradient-sanitized approach for learning differentially private generators D Chen, T Orekondy, M Fritz Advances in Neural Information Processing Systems (NeurIPS) 2020, 2020 | 152 | 2020 |
| Responsible disclosure of generative models using scalable fingerprinting N Yu, V Skripniuk, D Chen, L Davis, M Fritz International Conference on Learning Representations (ICLR) 2022, 2020 | 54 | 2020 |
| Relaxloss: Defending membership inference attacks without losing utility D Chen, N Yu, M Fritz International Conference on Learning Representations (ICLR) 2022, 2022 | 32 | 2022 |
| Private Set Generation with Discriminative Information D Chen, R Kerkouche, M Fritz Neural Information Processing Systems (NeurIPS), 2022 | 20 | 2022 |
| Privacy considerations for sharing genomics data M Oestreich, D Chen, JL Schultze, M Fritz, M Becker EXCLI journal 20, 1243, 2021 | 17 | 2021 |
| Data forensics in diffusion models: A systematic analysis of membership privacy D Zhu*, D Chen*, J Grossklags, M Fritz arXiv preprint arXiv:2302.07801, 2023 | 12 | 2023 |
| FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations HP Wang, D Chen, R Kerkouche, M Fritz arXiv preprint arXiv:2302.01068, 2023 | 3* | 2023 |
| MargCTGAN: A "Marginally'' Better CTGAN for the Low Sample Regime T Afonja, D Chen, M Fritz German Conference on Pattern Recognition (GCPR), 2023 | 2 | 2023 |
| PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics D Zhu, D Chen, Q Li, Z Chen, L Ma, J Grossklags, M Fritz arXiv preprint arXiv:2404.04722, 2024 | | 2024 |
| Towards Biologically Plausible and Private Gene Expression Data Generation D Chen, M Oestreich, T Afonja, R Kerkouche, M Becker, M Fritz arXiv preprint arXiv:2402.04912, 2024 | | 2024 |
| A Unified View of Differentially Private Deep Generative Modeling D Chen, R Kerkouche, M Fritz arXiv preprint arXiv:2309.15696, 2023 | | 2023 |
Mario FritzFaculty CISPA Helmholtz Center for Information Security; Professor Saarland UniversityVerified email at cispa.de
