| 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 | 225 | 2022 |
| Smooth Loss Functions for Deep Top-k Classification L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2018 | 141 | 2018 |
| Griffin: Mixing gated linear recurrences with local attention for efficient language models S De, SL Smith, A Fernando, A Botev, G Cristian-Muraru, A Gu, R Haroun, ... arXiv preprint arXiv:2402.19427, 2024 | 93 | 2024 |
| 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 | 68 | 2023 |
| Training neural networks for and by interpolation L Berrada, A Zisserman, MP Kumar International Conference on Machine Learning, 2020 | 68 | 2020 |
| Deep Frank-Wolfe For Neural Network Optimization L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2019 | 46 | 2019 |
| 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 | 23* | 2021 |
| Trusting SVM for piecewise linear CNNs L Berrada, A Zisserman, MP Kumar International Conference on Learning Representations, 2017 | 20 | 2017 |
| Convnets match vision transformers at scale SL Smith, A Brock, L Berrada, S De arXiv preprint arXiv:2310.16764, 2023 | 17 | 2023 |
| Unlocking accuracy and fairness in differentially private image classification L Berrada, S De, JH Shen, J Hayes, R Stanforth, D Stutz, P Kohli, ... arXiv preprint arXiv:2308.10888, 2023 | 15* | 2023 |
| Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models, Feb. 2024 S De, SL Smith, A Fernando, A Botev, G Cristian-Muraru, A Gu, R Haroun, ... URL http://arxiv. org/abs/2402.19427 v1, 0 | 13 | |
| Soham De. Convnets match vision transformers at scale SL Smith, A Brock, L Berrada arXiv preprint arXiv:2303.08774 3, 2023 | 8 | 2023 |
| Operationalizing contextual integrity in privacy-conscious assistants S Ghalebikesabi, E Bagdasaryan, R Yi, I Yona, I Shumailov, A Pappu, ... arXiv preprint arXiv:2408.02373, 2024 | 7 | 2024 |
| RecurrentGemma: Moving Past Transformers for Efficient Open Language Models A Botev, S De, SL Smith, A Fernando, GC Muraru, R Haroun, L Berrada, ... arXiv preprint arXiv:2404.07839, 2024 | 7 | 2024 |
| A Stochastic Bundle Method for Interpolation A Paren, L Berrada, RPK Poudel, MP Kumar Journal of Machine Learning Research 23 (15), 1-57, 2022 | 6 | 2022 |
| Comment on stochastic Polyak step-size: Performance of ALI-G L Berrada, A Zisserman, MP Kumar arXiv preprint arXiv:2105.10011, 2021 | 5 | 2021 |
| Leveraging structure for optimization in deep learning L Berrada University of Oxford, 2019 | | 2019 |
M. Pawan KumarGoogle DeepMindE-mailová adresa ověřena na: deepmind.com