| Very Deep Convolutional Networks for Large-Scale Image Recognition K Simonyan, A Zisserman arXiv preprint arXiv:1409.1556, 2014 | 50490 | 2014 |
| Two-stream convolutional networks for action recognition in videos K Simonyan, A Zisserman Advances in neural information processing systems 27, 568-576, 2014 | 4830 | 2014 |
| Mastering the game of go without human knowledge D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ... nature 550 (7676), 354-359, 2017 | 4769 | 2017 |
| Spatial Transformer Networks M Jaderberg, K Simonyan, A Zisserman, K Kavukcuoglu arXiv preprint arXiv:1506.02025, 2015 | 3715 | 2015 |
| Return of the Devil in the Details: Delving Deep into Convolutional Nets K Chatfield, K Simonyan, A Vedaldi, A Zisserman arXiv preprint arXiv:1405.3531, 2014 | 3054 | 2014 |
| Wavenet: A generative model for raw audio A Van Den Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, ... arXiv preprint arXiv:1609.03499, 2016 | 2557 | 2016 |
| Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps K Simonyan, A Vedaldi, A Zisserman arXiv preprint arXiv:1312.6034, 2013 | 2323 | 2013 |
| Large Scale GAN Training for High Fidelity Natural Image Synthesis A Brock, J Donahue, K Simonyan arXiv preprint arXiv:1809.11096, 2018 | 1429 | 2018 |
| DARTS: Differentiable Architecture Search H Liu, K Simonyan, Y Yang arXiv preprint arXiv:1806.09055, 2018 | 1156 | 2018 |
| The Kinetics Human Action Video Dataset W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ... arXiv preprint arXiv:1705.06950, 2017 | 1114 | 2017 |
| A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... Science 362 (6419), 1140-1144, 2018 | 1095 | 2018 |
| Deep inside convolutional networks: Visualising image classification models and saliency maps K Simonyan, A Vedaldi, A Zisserman Iclr, 2014 | 925 | 2014 |
| Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... arXiv preprint arXiv:1712.01815, 2017 | 867 | 2017 |
| Reading text in the wild with convolutional neural networks M Jaderberg, K Simonyan, A Vedaldi, A Zisserman International Journal of Computer Vision 116 (1), 1-20, 2016 | 828 | 2016 |
| Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition M Jaderberg, K Simonyan, A Vedaldi, A Zisserman arXiv preprint arXiv:1406.2227, 2014 | 570 | 2014 |
| Fisher Vector Faces in the Wild K Simonyan, OM Parkhi, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC) 2013, 2013 | 540 | 2013 |
| 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 | 525 | 2018 |
| Hierarchical Representations for Efficient Architecture Search H Liu, K Simonyan, O Vinyals, C Fernando, K Kavukcuoglu arXiv preprint arXiv:1711.00436, 2017 | 465 | 2017 |
| StarCraft II: A New Challenge for Reinforcement Learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 457 | 2017 |
| Parallel WaveNet: Fast High-Fidelity Speech Synthesis A Oord, Y Li, I Babuschkin, K Simonyan, O Vinyals, K Kavukcuoglu, ... arXiv preprint arXiv:1711.10433, 2017 | 400 | 2017 |
