| Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, D Wierstra Advances in neural information processing systems 29, 2016 | 4449 | 2016 |
| Simple and scalable predictive uncertainty estimation using deep ensembles B Lakshminarayanan, A Pritzel, C Blundell Advances in neural information processing systems 30, 2017 | 2736 | 2017 |
| Weight uncertainty in neural network C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra International conference on machine learning, 1613-1622, 2015 | 2301 | 2015 |
| Deep exploration via bootstrapped DQN I Osband, C Blundell, A Pritzel, B Van Roy Advances in neural information processing systems 29, 2016 | 970 | 2016 |
| Learning to reinforcement learn JX Wang, Z Kurth-Nelson, D Tirumala, H Soyer, JZ Leibo, R Munos, ... arXiv preprint arXiv:1611.05763, 2016 | 662 | 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 | 565 | 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 | 444 | 2018 |
| Noisy networks for exploration M Fortunato, MG Azar, B Piot, J Menick, I Osband, A Graves, V Mnih, ... arXiv preprint arXiv:1706.10295, 2017 | 436 | 2017 |
| 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 | 353 | 2019 |
| 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 | 331 | 2017 |
| 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 | 267 | 2020 |
| Neural episodic control A Pritzel, B Uria, S Srinivasan, AP Badia, O Vinyals, D Hassabis, ... International Conference on Machine Learning, 2827-2836, 2017 | 265 | 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 | 252 | 2014 |
| Model-free episodic control C Blundell, B Uria, A Pritzel, Y Li, A Ruderman, JZ Leibo, J Rae, ... arXiv preprint arXiv:1606.04460, 2016 | 223* | 2016 |
| Modelling reciprocating relationships with Hawkes processes C Blundell, J Beck, KA Heller Advances in neural information processing systems 25, 2012 | 213 | 2012 |
| Bayesian recurrent neural networks M Fortunato, C Blundell, O Vinyals arXiv preprint arXiv:1704.02798, 2017 | 186 | 2017 |
| 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 | 157 | 2016 |
| 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 | 113 | 2020 |
| Computations underlying social hierarchy learning: distinct neural mechanisms for updating and representing self-relevant information D Kumaran, A Banino, C Blundell, D Hassabis, P Dayan Neuron 92 (5), 1135-1147, 2016 | 105 | 2016 |
| Bayesian rose trees C Blundell, YW Teh, KA Heller Uncertainty in Artificial Intelligence, 2010 | 99 | 2010 |
Alexander PritzelDeepmindVerified email at google.com
