| Hybrid computing using a neural network with dynamic external memory A Graves, G Wayne, M Reynolds, T Harley, I Danihelka, ... Nature 538 (7626), 471-476, 2016 | 1162 | 2016 |
| Learning to learn by gradient descent by gradient descent M Andrychowicz, M Denil, S Gomez, MW Hoffman, D Pfau, T Schaul, ... arXiv preprint arXiv:1606.04474, 2016 | 1145 | 2016 |
| Policy distillation AA Rusu, SG Colmenarejo, C Gulcehre, G Desjardins, J Kirkpatrick, ... arXiv preprint arXiv:1511.06295, 2015 | 330 | 2015 |
| Learning to learn without gradient descent by gradient descent Y Chen, MW Hoffman, SG Colmenarejo, M Denil, TP Lillicrap, M Botvinick, ... International Conference on Machine Learning, 748-756, 2017 | 160* | 2017 |
| Parallel multiscale autoregressive density estimation S Reed, A Oord, N Kalchbrenner, SG Colmenarejo, Z Wang, Y Chen, ... International Conference on Machine Learning, 2912-2921, 2017 | 133 | 2017 |
| Learned optimizers that scale and generalize O Wichrowska, N Maheswaranathan, MW Hoffman, SG Colmenarejo, ... International Conference on Machine Learning, 3751-3760, 2017 | 119 | 2017 |
| Programmable agents M Denil, SG Colmenarejo, S Cabi, D Saxton, N de Freitas arXiv preprint arXiv:1706.06383, 2017 | 42 | 2017 |
| The intentional unintentional agent: Learning to solve many continuous control tasks simultaneously S Cabi, SG Colmenarejo, MW Hoffman, M Denil, Z Wang, N Freitas Conference on Robot Learning, 207-216, 2017 | 26 | 2017 |
| Acme: A research framework for distributed reinforcement learning M Hoffman, B Shahriari, J Aslanides, G Barth-Maron, F Behbahani, ... arXiv preprint arXiv:2006.00979, 2020 | 25 | 2020 |
| Learning awareness models B Amos, L Dinh, S Cabi, T Rothörl, SG Colmenarejo, A Muldal, T Erez, ... arXiv preprint arXiv:1804.06318, 2018 | 25 | 2018 |
| Tf-replicator: Distributed machine learning for researchers P Buchlovsky, D Budden, D Grewe, C Jones, J Aslanides, F Besse, ... arXiv preprint arXiv:1902.00465, 2019 | 21 | 2019 |
| Scaling data-driven robotics with reward sketching and batch reinforcement learning S Cabi, SG Colmenarejo, A Novikov, K Konyushkova, S Reed, R Jeong, ... arXiv preprint arXiv:1909.12200, 2019 | 20* | 2019 |
| Task-relevant adversarial imitation learning K Zolna, S Reed, A Novikov, SG Colmenarej, D Budden, S Cabi, M Denil, ... arXiv preprint arXiv:1910.01077, 2019 | 13 | 2019 |
| One-shot high-fidelity imitation: Training large-scale deep nets with rl TL Paine, SG Colmenarejo, Z Wang, S Reed, Y Aytar, T Pfaff, ... arXiv preprint arXiv:1810.05017, 2018 | 12 | 2018 |
| RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ... Advances in Neural Information Processing Systems 33, 2020 | 11* | 2020 |
| Visual Imitation with a Minimal Adversary S Reed, Y Aytar, Z Wang, T Paine, A van den Oord, T Pfaff, S Gomez, ... | 2 | 2018 |
| Approximate hubel-wiesel modules and the data structures of neural computation JZ Leibo, J Cornebise, S Gómez, D Hassabis arXiv preprint arXiv:1512.08457, 2015 | 2 | 2015 |
| Data-driven robot control S Cabi, Z Wang, A Novikov, K Konyushkova, SG Colmenarejo, SE Reed, ... US Patent App. 17/020,294, 2021 | | 2021 |
| Regularized Behavior Value Estimation C Gulcehre, SG Colmenarejo, Z Wang, J Sygnowski, T Paine, K Zolna, ... arXiv preprint arXiv:2103.09575, 2021 | | 2021 |
Nando de FreitasCIFAR & DeepMindVerified email at google.com
