| A clinically applicable approach to continuous prediction of future acute kidney injury N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ... Nature 572 (7767), 116-119, 2019 | 250 | 2019 |
| Model-free episodic control C Blundell, B Uria, A Pritzel, Y Li, A Ruderman, JZ Leibo, J Rae, ... arXiv preprint arXiv:1606.04460, 2016 | 160* | 2016 |
| Scaling memory-augmented neural networks with sparse reads and writes JW Rae, JJ Hunt, T Harley, I Danihelka, A Senior, G Wayne, A Graves, ... arXiv preprint arXiv:1610.09027, 2016 | 115 | 2016 |
| Relational recurrent neural networks A Santoro, R Faulkner, D Raposo, J Rae, M Chrzanowski, T Weber, ... arXiv preprint arXiv:1806.01822, 2018 | 112 | 2018 |
| Unsupervised predictive memory in a goal-directed agent G Wayne, CC Hung, D Amos, M Mirza, A Ahuja, A Grabska-Barwinska, ... arXiv preprint arXiv:1803.10760, 2018 | 104 | 2018 |
| Neural arithmetic logic units A Trask, F Hill, S Reed, J Rae, C Dyer, P Blunsom arXiv preprint arXiv:1808.00508, 2018 | 99 | 2018 |
| Compressive transformers for long-range sequence modelling JW Rae, A Potapenko, SM Jayakumar, TP Lillicrap arXiv preprint arXiv:1911.05507, 2019 | 51 | 2019 |
| Memory-based parameter adaptation P Sprechmann, SM Jayakumar, JW Rae, A Pritzel, AP Badia, B Uria, ... International Conference on Learning Representations, 2018 | 51 | 2018 |
| Fast parametric learning with activation memorization JW Rae, C Dyer, P Dayan, TP Lillicrap International Conference on Machine Learning 80, 4228-4237, 2018 | 31 | 2018 |
| Stabilizing transformers for reinforcement learning E Parisotto, F Song, J Rae, R Pascanu, C Gulcehre, S Jayakumar, ... International Conference on Machine Learning, 7487-7498, 2020 | 27 | 2020 |
| Training language gans from scratch CM d'Autume, M Rosca, J Rae, S Mohamed arXiv preprint arXiv:1905.09922, 2019 | 25 | 2019 |
| V-MPO: On-policy maximum a posteriori policy optimization for discrete and continuous control HF Song, A Abdolmaleki, JT Springenberg, A Clark, H Soyer, JW Rae, ... arXiv preprint arXiv:1909.12238, 2019 | 22 | 2019 |
| Multiplicative interactions and where to find them SM Jayakumar, WM Czarnecki, J Menick, J Schwarz, J Rae, S Osindero, ... International Conference on Learning Representations, 2019 | 21 | 2019 |
| Meta-Learning Neural Bloom Filters JW Rae, S Bartunov, TP Lillicrap International Conference on Machine Learning 2019, 2019 | 14 | 2019 |
| Reducing sentiment bias in language models via counterfactual evaluation PS Huang, H Zhang, R Jiang, R Stanforth, J Welbl, J Rae, V Maini, ... arXiv preprint arXiv:1911.03064, 2019 | 13 | 2019 |
| Meta-learning deep energy-based memory models S Bartunov, JW Rae, S Osindero, TP Lillicrap arXiv preprint arXiv:1910.02720, 2019 | 11 | 2019 |
| Top-KAST: Top-K Always Sparse Training S Jayakumar, R Pascanu, J Rae, S Osindero, E Elsen Advances in Neural Information Processing Systems 33, 2020 | 6 | 2020 |
| Do transformers need deep long-range memory JW Rae, A Razavi arXiv preprint arXiv:2007.03356, 2020 | 3 | 2020 |
| Data stream cardinality: An empirical study of theoretically optimal algorithms J Rae Master's thesis, University of Bristol, 2012 | 2 | 2012 |
| Neural networks with relational memory M Chrzanowski, JW Rae, R Faulkner, TG Weber, DN Raposo, AA Santoro US Patent 10,853,725, 2020 | 1 | 2020 |
