| On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International conference on machine learning, 1321-1330, 2017 | 3367 | 2017 |
| Countering adversarial images using input transformations C Guo, M Rana, M Cisse, L Van Der Maaten arXiv preprint arXiv:1711.00117, 2017 | 1134 | 2017 |
| Simple black-box adversarial attacks C Guo, J Gardner, Y You, AG Wilson, K Weinberger International Conference on Machine Learning, 2484-2493, 2019 | 319 | 2019 |
| An empirical study on evaluation metrics of generative adversarial networks Q Xu, G Huang, Y Yuan, C Guo, Y Sun, F Wu, K Weinberger arXiv preprint arXiv:1806.07755, 2018 | 247 | 2018 |
| Supervised word mover's distance G Huang, C Guo, MJ Kusner, Y Sun, F Sha, KQ Weinberger Advances in neural information processing systems 29, 2016 | 187 | 2016 |
| Certified data removal from machine learning models C Guo, T Goldstein, A Hannun, L Van Der Maaten arXiv preprint arXiv:1911.03030, 2019 | 121 | 2019 |
| Low frequency adversarial perturbation C Guo, JS Frank, KQ Weinberger arXiv preprint arXiv:1809.08758, 2018 | 110 | 2018 |
| A new defense against adversarial images: Turning a weakness into a strength S Hu, T Yu, C Guo, WL Chao, KQ Weinberger Advances in Neural Information Processing Systems 32, 2019 | 82 | 2019 |
| Discovering and exploiting additive structure for Bayesian optimization J Gardner, C Guo, K Weinberger, R Garnett, R Grosse Artificial Intelligence and Statistics, 1311-1319, 2017 | 79 | 2017 |
| React: Out-of-distribution detection with rectified activations Y Sun, C Guo, Y Li Advances in Neural Information Processing Systems 34, 144-157, 2021 | 78 | 2021 |
| Breaking the glass ceiling for embedding-based classifiers for large output spaces C Guo, A Mousavi, X Wu, DN Holtmann-Rice, S Kale, S Reddi, S Kumar Advances in Neural Information Processing Systems 32, 2019 | 42 | 2019 |
| Palindromic rich words and run-length encodings C Guo, J Shallit, AM Shur Information Processing Letters 116 (12), 735-738, 2016 | 27* | 2016 |
| On Hiding Neural Networks Inside Neural Networks C Guo, R Wu, KQ Weinberger arXiv preprint arXiv:2002.10078, 2020 | 26* | 2020 |
| Gradient-based adversarial attacks against text transformers C Guo, A Sablayrolles, H Jégou, D Kiela arXiv preprint arXiv:2104.13733, 2021 | 24 | 2021 |
| Secure multiparty computations in floating-point arithmetic C Guo, A Hannun, B Knott, L van der Maaten, M Tygert, R Zhu Information and Inference: A Journal of the IMA 11 (1), 103-135, 2022 | 19 | 2022 |
| On the importance of difficulty calibration in membership inference attacks L Watson, C Guo, G Cormode, A Sablayrolles arXiv preprint arXiv:2111.08440, 2021 | 17 | 2021 |
| Online adaptation to label distribution shift R Wu, C Guo, Y Su, KQ Weinberger Advances in Neural Information Processing Systems 34, 11340-11351, 2021 | 13 | 2021 |
| Measuring data leakage in machine-learning models with fisher information A Hannun, C Guo, L van der Maaten Uncertainty in Artificial Intelligence, 760-770, 2021 | 13 | 2021 |
| Making paper reviewing robust to bid manipulation attacks R Wu, C Guo, F Wu, R Kidambi, L Van Der Maaten, K Weinberger International Conference on Machine Learning, 11240-11250, 2021 | 13 | 2021 |
| On tight bounds for binary frameproof codes C Guo, DR Stinson, T Van Trung Designs, Codes and Cryptography 77, 301-319, 2015 | 12 | 2015 |
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
