Imagenet classification with deep convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton Advances in neural information processing systems 25, 2012 | 163753* | 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 | 53049 | 2014 |
Learning multiple layers of features from tiny images A Krizhevsky, G Hinton | 31140 | 2009 |
Improving neural networks by preventing co-adaptation of feature detectors GE Hinton arXiv preprint arXiv:1207.0580, 2012 | 11601 | 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 | 2752 | 2018 |
Advances in neural information processing systems A Krizhevsky (No Title), 1097, 2012 | 2068 | 2012 |
Transforming auto-encoders GE Hinton, A Krizhevsky, SD Wang Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011 | 1789 | 2011 |
One weird trick for parallelizing convolutional neural networks A Krizhevsky arXiv preprint arXiv:1404.5997, 2014 | 1598 | 2014 |
Learning multiple layers of features from tiny images.(2009) A Krizhevsky, G Hinton | 1534 | 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 | 1285 | 2010 |
The CIFAR-10 dataset A Krizhevsky, V Nair, G Hinton online: http://www. cs. toronto. edu/kriz/cifar. html 55 (5), 2, 2014 | 965 | 2014 |
Convolutional deep belief networks on cifar-10 A Krizhevsky, G Hinton Unpublished manuscript 40 (7), 1-9, 2010 | 943 | 2010 |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 | 861 | 2018 |
Using very deep autoencoders for content-based image retrieval. A Krizhevsky, GE Hinton ESANN 1, 2, 2011 | 586 | 2011 |
Gradient-based learning applied to document recognition A Krizhevsky, I Sutskever, GE Hinton Commun. Acm 60, 84-90, 2017 | 532 | 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 | 486 | 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 | 312 | 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 | 244 | 2012 |