| Smooth Loss Functions for Deep Top-k Classification L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2018 | 90 | 2018 |
| Deep Frank-Wolfe For Neural Network Optimization L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2019 | 38 | 2019 |
| Unlocking high-accuracy differentially private image classification through scale S De, L Berrada, J Hayes, SL Smith, B Balle arXiv preprint arXiv:2204.13650, 2022 | 34 | 2022 |
| Training neural networks for and by interpolation L Berrada, A Zisserman, MP Kumar International Conference on Machine Learning, 2020 | 31 | 2020 |
| Trusting SVM for piecewise linear CNNs L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2017 | 17 | 2017 |
| Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications L Berrada, S Dathathri, K Dvijotham, R Stanforth, RR Bunel, J Uesato, ... Advances in Neural Information Processing Systems 34, 11136-11147, 2021 | 10* | 2021 |
| A Stochastic Bundle Method for Interpolating Networks A Paren, L Berrada, RPK Poudel, MP Kumar Journal of Machine Learning Research 23, 1-57, 2022 | 2 | 2022 |
| Comment on Stochastic Polyak Step-Size: Performance of ALI-G L Berrada, A Zisserman, MP Kumar arXiv preprint arXiv:2105.10011, 2021 | 1 | 2021 |
| Differentially Private Diffusion Models Generate Useful Synthetic Images S Ghalebikesabi, L Berrada, S Gowal, I Ktena, R Stanforth, J Hayes, S De, ... arXiv preprint arXiv:2302.13861, 2023 | | 2023 |
| Leveraging structure for optimization in deep learning L Berrada University of Oxford, 2019 | | 2019 |
M. Pawan KumarDeepMindVerified email at deepmind.com
