| 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 | 1571 | 2016 |
| Flamingo: a visual language model for few-shot learning JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ... arXiv preprint arXiv:2204.14198, 2022 | 184 | 2022 |
| 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 | 160 | 2018 |
| Unsupervised learning of object keypoints for perception and control TD Kulkarni, A Gupta, C Ionescu, S Borgeaud, M Reynolds, A Zisserman, ... Advances in neural information processing systems 32, 2019 | 136 | 2019 |
| Capturing time-of-flight data with confidence M Reynolds, J Doboš, L Peel, T Weyrich, GJ Brostow CVPR 2011, 945-952, 2011 | 132 | 2011 |
| Convolution by evolution: Differentiable pattern producing networks C Fernando, D Banarse, M Reynolds, F Besse, D Pfau, M Jaderberg, ... Proceedings of the Genetic and Evolutionary Computation Conference 2016, 109-116, 2016 | 114 | 2016 |
| Multi-object datasets R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ... DeepMind 5 (6), 7, 2019 | 36 | 2019 |
| Attention over learned object embeddings enables complex visual reasoning D Ding, F Hill, A Santoro, M Reynolds, M Botvinick Advances in neural information processing systems 34, 9112-9124, 2021 | 24 | 2021 |
| Grabska-Barwi nska A Graves, G Wayne, M Reynolds, T Harley, I Danihelka A., Colmenarejo, SG, Grefenstette, E., Ramalho, T., Agapiou, J., et al, 471-476, 2016 | 24* | 2016 |
| Alchemy: A structured task distribution for meta-reinforcement learning JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ... arXiv preprint arXiv:2102.02926 262, 265-268, 2021 | 17 | 2021 |
| Representation matters: Improving perception and exploration for robotics M Wulfmeier, A Byravan, T Hertweck, I Higgins, A Gupta, T Kulkarni, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 6512-6519, 2021 | 10 | 2021 |
| Alignnet: Unsupervised entity alignment A Creswell, K Nikiforou, O Vinyals, A Saraiva, R Kabra, L Matthey, ... arXiv preprint arXiv:2007.08973, 2020 | 10 | 2020 |
| Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents JX Wang, M King, N Porcel, Z Kurth-Nelson, T Zhu, C Deck, P Choy, ... arXiv preprint arXiv:2102.02926, 2021 | 9 | 2021 |
| Augmenting neural networks with external memory AB Graves, I Danihelka, TJA Harley, MKC Reynolds, GD Wayne US Patent 10,832,134, 2020 | 7 | 2020 |
| Swipe mosaics from video M Reynolds, TSF Haines, GJ Brostow arXiv preprint arXiv:1609.08080, 2016 | 1 | 2016 |
| Augmenting neural networks with external memory AB Graves, I Danihelka, TJA Harley, MKC Reynolds, GD Wayne US Patent App. 17/093,373, 2021 | | 2021 |
| deepmin... Shell R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ... | | 2019 |
| deepmind/Multi_object_datasets R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ... | | 2019 |
| Python-Multi object datasets: Multi-object image datasets with ground-truth segmentation masks and generative factors. R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ... | | 2019 |
| Multi-object image datasets with ground-truth segmentation masks and generative factors. R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ... | | 2019 |
Alex GravesUniversity of TorontoПотвърден имейл адрес: cs.toronto.edu
