| Asynchronous methods for deep reinforcement learning V Mnih, AP Badia, M Mirza, A Graves, T Lillicrap, T Harley, D Silver, ... International Conference on Machine Learning, 1928-1937, 2016 | 8515 | 2016 |
| 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 | 1609 | 2016 |
| Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures L Espeholt, H Soyer, R Munos, K Simonyan, V Mnih, T Ward, Y Doron, ... International Conference on Machine Learning, 1407-1416, 2018 | 1207 | 2018 |
| The predictron: End-to-end learning and planning D Silver, H Hasselt, M Hessel, T Schaul, A Guez, T Harley, ... International Conference on Machine Learning, 3191-3199, 2017 | 260 | 2017 |
| Scaling memory-augmented neural networks with sparse reads and writes J Rae, JJ Hunt, I Danihelka, T Harley, AW Senior, G Wayne, A Graves, ... Advances in Neural Information Processing Systems, 3621-3629, 2016 | 166 | 2016 |
| 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 | 79 | 2019 |
| Dynamic control flow in large-scale machine learning Y Yu, M Abadi, P Barham, E Brevdo, M Burrows, A Davis, J Dean, ... Proceedings of the Thirteenth EuroSys Conference, 1-15, 2018 | 75 | 2018 |
| A generalized framework for population based training A Li, O Spyra, S Perel, V Dalibard, M Jaderberg, C Gu, D Budden, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 52 | 2019 |
| Imitating interactive intelligence J Abramson, A Ahuja, I Barr, A Brussee, F Carnevale, M Cassin, ... arXiv preprint arXiv:2012.05672, 2020 | 45 | 2020 |
| Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text F Hill, S Mokra, N Wong, T Harley arXiv preprint arXiv:2005.09382, 2020 | 44 | 2020 |
| Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning DMIA Team, J Abramson, A Ahuja, A Brussee, F Carnevale, M Cassin, ... arXiv preprint arXiv:2112.03763, 2021 | 13 | 2021 |
| Asynchronous deep reinforcement learning V Mnih, AP Badia, AB Graves, TJA Harley, D Silver, K Kavukcuoglu US Patent 10,936,946, 2021 | 11 | 2021 |
| Asynchronous deep reinforcement learning V Mnih, AP Badia, AB Graves, TJA Harley, D Silver, K Kavukcuoglu US Patent App. 10/346,741, 2019 | 9* | 2019 |
| Augmenting neural networks with external memory AB Graves, I Danihelka, TJA Harley, MKC Reynolds, GD Wayne US Patent 10,832,134, 2020 | 7 | 2020 |
| Asynchronous deep reinforcement learning V Mnih, AP Badia, AB Graves, TJA Harley, D Silver, K Kavukcuoglu US Patent 10,346,741, 2019 | 4 | 2019 |
| Robust Instruction-Following in a Situated Agent via Transfer-Learning from Text F Hill, S Mokra, N Wong, T Harley | 1 | 2019 |
| Population Based Training as a Service A Li, O Spyra, S Perel, V Dalibard, M Jaderberg, C Gu, D Budden, ... NIPS Systems for ML Workshop, Montréal, Canada, 2018 | 1 | 2018 |
| Asynchronous deep reinforcement learning V Mnih, AP Badia, AB Graves, TJA Harley, D Silver, K Kavukcuoglu US Patent 11,334,792, 2022 | | 2022 |
| Augmenting neural networks with sparsely-accessed external memory I Danihelka, GD Wayne, FM Wang, ET Grefenstette, JW Rae, AB Graves, ... US Patent 11,151,443, 2021 | | 2021 |
| Asynchronous deep reinforcement learning V Mnih, AP Badia, AB Graves, TJA Harley, D Silver, K Kavukcuoglu US Patent App. 17/170,316, 2021 | | 2021 |
