Karen Simonyan
Karen Simonyan
Chief Scientist, Microsoft AI
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Cited by
Cited by
Very Deep Convolutional Networks for Large-Scale Image Recognition
K Simonyan, A Zisserman
arXiv preprint arXiv:1409.1556, 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
Two-stream convolutional networks for action recognition in videos
K Simonyan, A Zisserman
Advances in neural information processing systems 27, 568-576, 2014
Spatial Transformer Networks
M Jaderberg, K Simonyan, A Zisserman, K Kavukcuoglu
arXiv preprint arXiv:1506.02025, 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
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
K Simonyan, A Vedaldi, A Zisserman
arXiv preprint arXiv:1312.6034, 2013
Large Scale GAN Training for High Fidelity Natural Image Synthesis
A Brock, J Donahue, K Simonyan
arXiv preprint arXiv:1809.11096, 2018
DARTS: Differentiable Architecture Search
H Liu, K Simonyan, Y Yang
arXiv preprint arXiv:1806.09055, 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
The Kinetics Human Action Video Dataset
W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ...
arXiv preprint arXiv:1705.06950, 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
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
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
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
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
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
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
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
Training Compute-Optimal Large Language Models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
Hierarchical Representations for Efficient Architecture Search
H Liu, K Simonyan, O Vinyals, C Fernando, K Kavukcuoglu
arXiv preprint arXiv:1711.00436, 2017
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