Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, D Wierstra Advances in neural information processing systems 29, 2016 | 7967 | 2016 |
Simple and scalable predictive uncertainty estimation using deep ensembles B Lakshminarayanan, A Pritzel, C Blundell Advances in neural information processing systems 30, 2017 | 5735 | 2017 |
Weight uncertainty in neural network C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra International conference on machine learning, 1613-1622, 2015 | 3906 | 2015 |
Deep exploration via bootstrapped DQN I Osband, C Blundell, A Pritzel, B Van Roy Advances in neural information processing systems 29, 2016 | 1445 | 2016 |
Learning to reinforcement learn JX Wang, Z Kurth-Nelson, D Tirumala, H Soyer, JZ Leibo, R Munos, ... arXiv preprint arXiv:1611.05763, 2016 | 1021 | 2016 |
Pathnet: Evolution channels gradient descent in super neural networks C Fernando, D Banarse, C Blundell, Y Zwols, D Ha, AA Rusu, A Pritzel, ... arXiv preprint arXiv:1701.08734, 2017 | 960 | 2017 |
Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 711 | 2018 |
Reinforcement learning, fast and slow M Botvinick, S Ritter, JX Wang, Z Kurth-Nelson, C Blundell, D Hassabis Trends in cognitive sciences 23 (5), 408-422, 2019 | 682 | 2019 |
Agent57: Outperforming the atari human benchmark AP Badia, B Piot, S Kapturowski, P Sprechmann, A Vitvitskyi, ZD Guo, ... International conference on machine learning, 507-517, 2020 | 627 | 2020 |
Darla: Improving zero-shot transfer in reinforcement learning I Higgins, A Pal, A Rusu, L Matthey, C Burgess, A Pritzel, M Botvinick, ... International Conference on Machine Learning, 1480-1490, 2017 | 498 | 2017 |
Advancing mathematics by guiding human intuition with AI A Davies, P Veličković, L Buesing, S Blackwell, D Zheng, N Tomašev, ... Nature 600 (7887), 70-74, 2021 | 426 | 2021 |
Neural episodic control A Pritzel, B Uria, S Srinivasan, AP Badia, O Vinyals, D Hassabis, ... International conference on machine learning, 2827-2836, 2017 | 402 | 2017 |
Deep AutoRegressive Networks K Gregor, I Danihelka, A Mnih, C Blundell, D Wierstra Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014 | 335 | 2014 |
Never give up: Learning directed exploration strategies AP Badia, P Sprechmann, A Vitvitskyi, D Guo, B Piot, S Kapturowski, ... arXiv preprint arXiv:2002.06038, 2020 | 322 | 2020 |
Model-free episodic control C Blundell, B Uria, A Pritzel, Y Li, A Ruderman, JZ Leibo, J Rae, ... arXiv preprint arXiv:1606.04460, 2016 | 293 | 2016 |
Bayesian recurrent neural networks M Fortunato, C Blundell, O Vinyals arXiv preprint arXiv:1704.02798, 2017 | 253 | 2017 |
Modelling reciprocating relationships with Hawkes processes C Blundell, J Beck, KA Heller Advances in neural information processing systems 25, 2012 | 252 | 2012 |
Representation learning via invariant causal mechanisms J Mitrovic, B McWilliams, J Walker, L Buesing, C Blundell arXiv preprint arXiv:2010.07922, 2020 | 219 | 2020 |
Early visual concept learning with unsupervised deep learning I Higgins, L Matthey, X Glorot, A Pal, B Uria, C Blundell, S Mohamed, ... arXiv preprint arXiv:1606.05579, 2016 | 196 | 2016 |
Neural execution of graph algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell arXiv preprint arXiv:1910.10593, 2019 | 170 | 2019 |