| Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ... Nature 518 (7540), 529-533, 2015 | 32915 | 2015 |
| Playing Atari with Deep Reinforcement Learning V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ... arXiv preprint arXiv:1312.5602, 2013 | 16408 | 2013 |
| 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 | 12077 | 2016 |
| Recurrent Models of Visual Attention V Mnih, N Heess, A Graves, K Kavukcuoglu Advances in Neural Information Processing Systems, 2204-2212, 2014 | 4936 | 2014 |
| 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, ... arXiv preprint arXiv:1802.01561, 2018 | 1727 | 2018 |
| Reinforcement learning with unsupervised auxiliary tasks M Jaderberg, V Mnih, WM Czarnecki, T Schaul, JZ Leibo, D Silver, ... arXiv preprint arXiv:1611.05397, 2016 | 1452 | 2016 |
| Multiple Object Recognition with Visual Attention J Ba, V Mnih, K Kavukcuoglu arXiv preprint arXiv:1412.7755, 2014 | 1295 | 2014 |
| Sample Efficient Actor-Critic with Experience Replay Z Wang, V Bapst, N Heess, V Mnih, R Munos, K Kavukcuoglu, ... arXiv preprint arXiv:1611.01224, 2016 | 1043 | 2016 |
| Machine Learning for Aerial Image Labeling V Mnih University of Toronto, 2013 | 1003 | 2013 |
| Policy Distillation AA Rusu, SG Colmenarejo, C Gulcehre, G Desjardins, J Kirkpatrick, ... arXiv preprint arXiv:1511.06295, 2015 | 839 | 2015 |
| Learning to detect roads in high-resolution aerial images V Mnih, GE Hinton European Conference on Computer Vision, 210-223, 2010 | 782 | 2010 |
| Massively Parallel Methods for Deep Reinforcement Learning A Nair, P Srinivasan, S Blackwell, C Alcicek, R Fearon, A De Maria, ... arXiv preprint arXiv:1507.04296, 2015 | 655 | 2015 |
| Learning to Label Aerial Images from Noisy Data V Mnih, GE Hinton Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012 | 509 | 2012 |
| Learning by Playing-Solving Sparse Reward Tasks from Scratch M Riedmiller, R Hafner, T Lampe, M Neunert, J Degrave, T Van de Wiele, ... arXiv preprint arXiv:1802.10567, 2018 | 508 | 2018 |
| On deep generative models with applications to recognition MA Ranzato, J Susskind, V Mnih, G Hinton Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on …, 2011 | 303 | 2011 |
| Using Fast Weights to Attend to the Recent Past J Ba, GE Hinton, V Mnih, JZ Leibo, C Ionescu Advances In Neural Information Processing Systems, 4331-4339, 2016 | 284 | 2016 |
| Empirical bernstein stopping V Mnih, C Szepesvári, JY Audibert Proceedings of the 25th international conference on Machine learning, 672-679, 2008 | 280 | 2008 |
| The Uncertainty Bellman Equation and Exploration B O'Donoghue, I Osband, R Munos, V Mnih arXiv preprint arXiv:1709.05380, 2017 | 239 | 2017 |
| METHODS AND APPARATUS FOR REINFORCEMENT LEARNING V Mnih, K Kavukcuoglu US Patent 20,150,100,530, 2015 | 225 | 2015 |
| 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, 10724-10734, 2019 | 221 | 2019 |
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