Very Deep Convolutional Networks for Large-Scale Image Recognition K Simonyan, A Zisserman arXiv preprint arXiv:1409.1556, 2014 | 135501 | 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 | 11661 | 2017 |
Two-stream convolutional networks for action recognition in videos K Simonyan, A Zisserman Advances in neural information processing systems 27, 568-576, 2014 | 9736 | 2014 |
Spatial Transformer Networks M Jaderberg, K Simonyan, A Zisserman, K Kavukcuoglu arXiv preprint arXiv:1506.02025, 2015 | 9575 | 2015 |
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 | 9405* | 2016 |
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps K Simonyan, A Vedaldi, A Zisserman arXiv preprint arXiv:1312.6034, 2013 | 9073 | 2013 |
Large Scale GAN Training for High Fidelity Natural Image Synthesis A Brock, J Donahue, K Simonyan arXiv preprint arXiv:1809.11096, 2018 | 6371 | 2018 |
DARTS: Differentiable Architecture Search H Liu, K Simonyan, Y Yang arXiv preprint arXiv:1806.09055, 2018 | 5360 | 2018 |
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 | 4941 | 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 | 4761 | 2017 |
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 | 4363 | 2014 |
Improved protein structure prediction using potentials from deep learning AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Nature 577 (7792), 706-710, 2020 | 3416 | 2020 |
Flamingo: a visual language model for few-shot learning JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ... Advances in neural information processing systems 35, 23716-23736, 2022 | 3308 | 2022 |
Mastering atari, go, chess and shogi by planning with a learned model J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ... Nature 588 (7839), 604-609, 2020 | 2628 | 2020 |
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 | 2428 | 2017 |
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 | 1727 | 2018 |
Training Compute-Optimal Large Language Models J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ... arXiv preprint arXiv:2203.15556, 2022 | 1625 | 2022 |
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 | 1418 | 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 | 1226 | 2014 |
Hierarchical Representations for Efficient Architecture Search H Liu, K Simonyan, O Vinyals, C Fernando, K Kavukcuoglu arXiv preprint arXiv:1711.00436, 2017 | 1144 | 2017 |