| Integrative analysis of 111 reference human epigenomes A Kundaje, W Meuleman, J Ernst, M Bilenky, A Yen, P Kheradpour, ... Nature 518 (7539), 317, 2015 | 7052 | 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 | 880 | 2012 |
| Can AI-generated text be reliably detected? VS Sadasivan, A Kumar, S Balasubramanian, W Wang, S Feizi arXiv preprint arXiv:2303.11156, 2023 | 649 | 2023 |
| Are adversarial examples inevitable? A Shafahi, WR Huang, C Studer, S Feizi, T Goldstein arXiv preprint arXiv:1809.02104, 2018 | 415 | 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 | 351 | 2013 |
| Influence functions in deep learning are fragile S Basu, P Pope, S Feizi arXiv preprint arXiv:2006.14651, 2020 | 331 | 2020 |
| Adversarially robust distillation M Goldblum, L Fowl, S Feizi, T Goldstein Proceedings of the AAAI conference on artificial intelligence 34 (04), 3996-4003, 2020 | 326 | 2020 |
| Certifying llm safety against adversarial prompting A Kumar, C Agarwal, S Srinivas, AJ Li, S Feizi, H Lakkaraju arXiv preprint arXiv:2309.02705, 2023 | 303 | 2023 |
| Perceptual adversarial robustness: Defense against unseen threat models C Laidlaw, S Singla, S Feizi arXiv preprint arXiv:2006.12655, 2020 | 298 | 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 | 288 | 2020 |
| Deep partition aggregation: Provable defense against general poisoning attacks A Levine, S Feizi arXiv preprint arXiv:2006.14768, 2020 | 195 | 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, ... European Conference on Computer Vision, 55-70, 2020 | 182 | 2020 |
| 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 | 159 | 2022 |
| Quantum Wasserstein generative adversarial networks S Chakrabarti, H Yiming, T Li, S Feizi, X Wu Advances in Neural Information Processing Systems 32, 2019 | 157 | 2019 |
| Identifying and mitigating the security risks of generative ai C Barrett, B Boyd, E Bursztein, N Carlini, B Chen, J Choi, AR Chowdhury, ... Foundations and Trends® in Privacy and Security 6 (1), 1-52, 2023 | 153 | 2023 |
| 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 | 148 | 2020 |
| Salient imagenet: How to discover spurious features in deep learning? S Singla, S Feizi arXiv preprint arXiv:2110.04301, 2021 | 144 | 2021 |
| Improving deep learning interpretability by saliency guided training AA Ismail, H Corrada Bravo, S Feizi Advances in Neural Information Processing Systems 34, 26726-26739, 2021 | 139 | 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 | 135 | 2021 |
| 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 | 132 | 2020 |
