| Integrative analysis of 111 reference human epigenomes Roadmap Epigenomics Consortium Integrative analysis coordination Kundaje ... Nature 518 (7539), 317-330, 2015 | 6412* | 2015 |
| Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay A Melnikov, A Murugan, X Zhang, T Tesileanu, L Wang, P Rogov, S Feizi, ... Nature biotechnology 30 (3), 271-277, 2012 | 796 | 2012 |
| Can AI-generated text be reliably detected? VS Sadasivan, A Kumar, S Balasubramanian, W Wang, S Feizi arXiv preprint arXiv:2303.11156, 2023 | 441 | 2023 |
| Are adversarial examples inevitable? A Shafahi, WR Huang, C Studer, S Feizi, T Goldstein arXiv preprint arXiv:1809.02104, 2018 | 386 | 2018 |
| Network deconvolution as a general method to distinguish direct dependencies in networks S Feizi, D Marbach, M Médard, M Kellis Nature biotechnology 31 (8), 726-733, 2013 | 337 | 2013 |
| Adversarially robust distillation M Goldblum, L Fowl, S Feizi, T Goldstein Proceedings of the AAAI conference on artificial intelligence 34 (04), 3996-4003, 2020 | 253 | 2020 |
| Influence functions in deep learning are fragile S Basu, P Pope, S Feizi arXiv preprint arXiv:2006.14651, 2020 | 243 | 2020 |
| Perceptual adversarial robustness: Defense against unseen threat models C Laidlaw, S Singla, S Feizi arXiv preprint arXiv:2006.12655, 2020 | 238 | 2020 |
| Benchmarking deep learning interpretability in time series predictions AA Ismail, M Gunady, H Corrada Bravo, S Feizi Advances in neural information processing systems 33, 6441-6452, 2020 | 223 | 2020 |
| Functional adversarial attacks C Laidlaw, S Feizi Advances in neural information processing systems 32, 2019 | 223 | 2019 |
| Certifying llm safety against adversarial prompting A Kumar, C Agarwal, S Srinivas, AJ Li, S Feizi, H Lakkaraju arXiv preprint arXiv:2309.02705, 2023 | 164 | 2023 |
| Deep partition aggregation: Provable defense against general poisoning attacks A Levine, S Feizi arXiv preprint arXiv:2006.14768, 2020 | 159 | 2020 |
| Deep k-NN Defense Against Clean-Label Data Poisoning Attacks N Peri, N Gupta, WR Huang, L Fowl, C Zhu, S Feizi, T Goldstein, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 144 | 2020 |
| Quantum Wasserstein generative adversarial networks S Chakrabarti, H Yiming, T Li, S Feizi, X Wu Advances in Neural Information Processing Systems 32, 2019 | 123 | 2019 |
| Robust optimal transport with applications in generative modeling and domain adaptation Y Balaji, R Chellappa, S Feizi Advances in Neural Information Processing Systems 33, 12934-12944, 2020 | 121 | 2020 |
| Understanding GANs in the LQG setting: Formulation, generalization and stability S Feizi, F Farnia, T Ginart, D Tse IEEE Journal on Selected Areas in Information Theory 1 (1), 304-311, 2020 | 114* | 2020 |
| Robustness certificates for sparse adversarial attacks by randomized ablation A Levine, S Feizi Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4585-4593, 2020 | 114 | 2020 |
| Salient imagenet: How to discover spurious features in deep learning? S Singla, S Feizi arXiv preprint arXiv:2110.04301, 2021 | 112 | 2021 |
| Fairness through robustness: Investigating robustness disparity in deep learning V Nanda, S Dooley, S Singla, S Feizi, JP Dickerson Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021 | 112 | 2021 |
| Segment and complete: Defending object detectors against adversarial patch attacks with robust patch detection J Liu, A Levine, CP Lau, R Chellappa, S Feizi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 105 | 2022 |