| Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... nature 596 (7873), 583-589, 2021 | 27181 | 2021 |
| Conditional random fields as recurrent neural networks S Zheng, S Jayasumana, B Romera-Paredes, V Vineet, Z Su, D Du, ... Proceedings of the IEEE international conference on computer vision, 1529-1537, 2015 | 3302 | 2015 |
| International evaluation of an AI system for breast cancer screening SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ... Nature 577 (7788), 89-94, 2020 | 2522 | 2020 |
| Clinically applicable deep learning for diagnosis and referral in retinal disease J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ... Nature medicine 24 (9), 1342-1350, 2018 | 2424 | 2018 |
| Highly accurate protein structure prediction for the human proteome K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A Žídek, ... Nature 596 (7873), 590-596, 2021 | 2279 | 2021 |
| An embarrassingly simple approach to zero-shot learning B Romera-Paredes, P Torr International conference on machine learning, 2152-2161, 2015 | 1512 | 2015 |
| A probabilistic u-net for segmentation of ambiguous images S Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ... Advances in neural information processing systems 31, 2018 | 608 | 2018 |
| Discovering faster matrix multiplication algorithms with reinforcement learning A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ... Nature 610 (7930), 47-53, 2022 | 561 | 2022 |
| The benefit of multitask representation learning A Maurer, M Pontil, B Romera-Paredes Journal of Machine Learning Research 17 (81), 1-32, 2016 | 408 | 2016 |
| Recurrent instance segmentation B Romera-Paredes, PHS Torr Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 406 | 2016 |
| Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ... arXiv preprint arXiv:1809.04430, 2018 | 355 | 2018 |
| Applying and improving AlphaFold at CASP14 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021 | 312 | 2021 |
| High accuracy protein structure prediction using deep learning J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... Fourteenth critical assessment of techniques for protein structure …, 2020 | 228* | 2020 |
| The automatic detection of chronic pain-related expression: requirements, challenges and the multimodal EmoPain dataset MSH Aung, S Kaltwang, B Romera-Paredes, B Martinez, A Singh, M Cella, ... IEEE transactions on affective computing 7 (4), 435-451, 2015 | 219 | 2015 |
| Sparse coding for multitask and transfer learning A Maurer, M Pontil, B Romera-Paredes International conference on machine learning, 343-351, 2013 | 219 | 2013 |
| A new convex relaxation for tensor completion B Romera-Paredes, M Pontil Advances in neural information processing systems 26, 2013 | 203 | 2013 |
| Mathematical discoveries from program search with large language models B Romera-Paredes, M Barekatain, A Novikov, M Balog, MP Kumar, ... Nature 625 (7995), 468-475, 2024 | 197 | 2024 |
| Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study S Nikolov, S Blackwell, A Zverovitch, R Mendes, M Livne, J De Fauw, ... Journal of medical Internet research 23 (7), e26151, 2021 | 196 | 2021 |
| Multilinear multitask learning B Romera-Paredes, H Aung, N Bianchi-Berthouze, M Pontil International Conference on Machine Learning, 1444-1452, 2013 | 194 | 2013 |
| Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ... IEEE Signal Processing Magazine 35 (1), 37-52, 2018 | 172 | 2018 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
