| Imagenet classification with deep convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton Advances in neural information processing systems 25, 2012 | 166183* | 2012 |
| Dropout: a simple way to prevent neural networks from overfitting N Srivastava, G Hinton, A Krizhevsky, I Sutskever, R Salakhutdinov The journal of machine learning research 15 (1), 1929-1958, 2014 | 53909 | 2014 |
| Learning multiple layers of features from tiny images A Krizhevsky, G Hinton | 31943 | 2009 |
| Improving neural networks by preventing co-adaptation of feature detectors GE Hinton arXiv preprint arXiv:1207.0580, 2012 | 11719 | 2012 |
| Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection S Levine, P Pastor, A Krizhevsky, J Ibarz, D Quillen The International journal of robotics research 37 (4-5), 421-436, 2018 | 2814 | 2018 |
| Advances in neural information processing systems A Krizhevsky (No Title), 1097, 2012 | 2102 | 2012 |
| Transforming auto-encoders GE Hinton, A Krizhevsky, SD Wang Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011 | 1803 | 2011 |
| One weird trick for parallelizing convolutional neural networks A Krizhevsky arXiv preprint arXiv:1404.5997, 2014 | 1619 | 2014 |
| Learning multiple layers of features from tiny images.(2009) A Krizhevsky, G Hinton | 1616 | 2009 |
| Cifar-10 (canadian institute for advanced research) A Krizhevsky, V Nair, G Hinton URL http://www. cs. toronto. edu/kriz/cifar. html 5 (4), 1, 2010 | 1324 | 2010 |
| The CIFAR-10 dataset A Krizhevsky, V Nair, G Hinton online: http://www. cs. toronto. edu/kriz/cifar. html 55 (5), 2, 2014 | 977 | 2014 |
| Convolutional deep belief networks on cifar-10 A Krizhevsky, G Hinton Unpublished manuscript 40 (7), 1-9, 2010 | 949 | 2010 |
| Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst M Bansal, A Krizhevsky, A Ogale arXiv preprint arXiv:1812.03079, 2018 | 884 | 2018 |
| Using very deep autoencoders for content-based image retrieval. A Krizhevsky, GE Hinton ESANN 1, 2, 2011 | 593 | 2011 |
| Gradient-based learning applied to document recognition A Krizhevsky, I Sutskever, GE Hinton Commun. Acm 60, 84-90, 2017 | 544 | 2017 |
| Cifar-10 and cifar-100 datasets A Krizhevsky, V Nair, G Hinton URl: https://www. cs. toronto. edu/kriz/cifar. html 6 (1), 1, 2009 | 498 | 2009 |
| Real-time pedestrian detection with deep network cascades. A Angelova, A Krizhevsky, V Vanhoucke, AS Ogale, D Ferguson Bmvc 2, 4, 2015 | 322 | 2015 |
| Improving neural networks by preventing co-adaptation of feature detectors. arXiv 2012 GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov arXiv preprint arXiv:1207.0580, 2012 | 315 | 2012 |
| Factored 3-way restricted boltzmann machines for modeling natural images MA Ranzato, A Krizhevsky, G Hinton Proceedings of the thirteenth international conference on artificial …, 2010 | 300 | 2010 |
| Imagenet classification with deep convolutional neural networks GE Hinton, A Krizhevsky, I Sutskever Advances in neural information processing systems 25 (1106-1114), 1, 2012 | 248 | 2012 |
