| Imagenet classification with deep convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton Advances in neural information processing systems 25, 2012 | 154352* | 2012 |
| Deep learning Y LeCun, Y Bengio, G Hinton Nature 521 (7553), 436-44, 2015 | 76635 | 2015 |
| Learning internal representations by error-propagation DE Rumelhart, GE Hinton, RJ Williams Parallel Distributed Processing: Explorations in the Microstructure of …, 1986 | 58190* | 1986 |
| 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 | 50031 | 2014 |
| Visualizing data using t-SNE L van der Maaten, G Hinton Journal of Machine Learning Research 9 (Nov), 2579-2605, 2008 | 45580 | 2008 |
| Learning representations by back-propagating errors DE Rumelhart, GE Hinton, RJ Williams Nature 323 (6088), 533-536, 1986 | 37681 | 1986 |
| Learning multiple layers of features from tiny images A Krizhevsky, G Hinton | 29160 | 2009 |
| Rectified linear units improve restricted boltzmann machines V Nair, GE Hinton Proceedings of the 27th international conference on machine learning (ICML …, 2010 | 24651 | 2010 |
| Reducing the dimensionality of data with neural networks GE Hinton, RR Salakhutdinov Science 313 (5786), 504-507, 2006 | 22511 | 2006 |
| A fast learning algorithm for deep belief nets GE Hinton, S Osindero, YW Teh Neural computation 18 (7), 1527-1554, 2006 | 21178 | 2006 |
| Distilling the knowledge in a neural network G Hinton, O Vinyals, J Dean arXiv preprint arXiv:1503.02531, 2015 | 19041 | 2015 |
| A simple framework for contrastive learning of visual representations T Chen, S Kornblith, M Norouzi, G Hinton International conference on machine learning, 1597-1607, 2020 | 16438 | 2020 |
| Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ... IEEE Signal processing magazine 29 (6), 82-97, 2012 | 13204 | 2012 |
| Layer normalization JL Ba, JR Kiros, GE Hinton arXiv preprint arXiv:1607.06450, 2016 | 11313 | 2016 |
| Speech recognition with deep recurrent neural networks A Graves, A Mohamed, G Hinton 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 11296 | 2013 |
| Improving neural networks by preventing co-adaptation of feature detectors GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov arXiv preprint arXiv:1207.0580, 2012 | 11119 | 2012 |
| Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude T Tieleman, G Hinton Coursera: Neural networks for machine learning, 2012 | 7710 | 2012 |
| Schemata and sequential thought processes in PDP models. D Rumelhart, P Smolenksy, J McClelland, G Hinton Parallel distributed processing: Explorations in the microstructure of …, 1986 | 7490* | 1986 |
| Training products of experts by minimizing contrastive divergence GE Hinton Neural computation 14 (8), 1771-1800, 2002 | 6403 | 2002 |
| On the importance of initialization and momentum in deep learning I Sutskever, J Martens, G Dahl, G Hinton International conference on machine learning, 1139-1147, 2013 | 6121 | 2013 |
| Adaptive mixtures of local experts RA Jacobs, MI Jordan, SJ Nowlan, GE Hinton Neural computation 3 (1), 79-87, 1991 | 5849 | 1991 |
| Dynamic routing between capsules S Sabour, N Frosst, GE Hinton Advances in neural information processing systems 30, 2017 | 5674 | 2017 |
| A learning algorithm for Boltzmann machines DH Ackley, GE Hinton, TJ Sejnowski Cognitive science 9 (1), 147-169, 1985 | 5630 | 1985 |
| A practical guide to training restricted Boltzmann machines G Hinton | 4232 | 2010 |
| Phoneme recognition using time-delay neural networks A Waibel, T Hanazawa, G Hinton, K Shikano, KJ Lang Backpropagation, 35-61, 2013 | 4159 | 2013 |
| Deep Boltzmann machines R Salakhutdinov, G Hinton Artificial Intelligence and Statistics, 2009 | 3895* | 2009 |
| A view of the EM algorithm that justifies incremental, sparse, and other variants RM Neal, GE Hinton Learning in graphical models, 355-368, 1998 | 3664 | 1998 |
| Advances in neural information processing systems 22 DD Lee, P Pham, Y Largman, A Ng Tech Rep, 2009 | 2944* | 2009 |
| Neighbourhood components analysis J Goldberger, GE Hinton, S Roweis, RR Salakhutdinov Advances in neural information processing systems 17, 2004 | 2811 | 2004 |
| Connectionist learning procedures GE Hinton Machine learning, 555-610, 1990 | 2644 | 1990 |
| Restricted Boltzmann machines for collaborative filtering R Salakhutdinov, A Mnih, G Hinton Proceedings of the 24th international conference on Machine learning, 791-798, 2007 | 2586 | 2007 |
| The CIFAR-10 dataset A Krizhevsky, V Nair, G Hinton online: http://www. cs. toronto. edu/kriz/cifar. html 55 (5), 2, 2014 | 2485* | 2014 |
| Learning and relearning in Boltzmann machines GE Hinton, TJ Sejnowski Parallel distributed processing: Explorations in the microstructure of …, 1986 | 2353 | 1986 |
| Distributed representations GE Hinton, JL McClelland, DE Rumelhart Parallel distributed processing: Explorations in the microstructure of …, 1986 | 2180 | 1986 |
| Big self-supervised models are strong semi-supervised learners T Chen, S Kornblith, K Swersky, M Norouzi, GE Hinton Advances in neural information processing systems 33, 22243-22255, 2020 | 2157 | 2020 |
| Acoustic modeling using deep belief networks A Mohamed, G Dahl, G Hinton Audio, Speech, and Language Processing, IEEE Transactions on 20, 14-22, 2012 | 2155 | 2012 |
| Neural networks for machine learning lecture 6a overview of mini-batch gradient descent G Hinton, N Srivastava, K Swersky Cited on 14 (8), 2, 2012 | 2119 | 2012 |
| Generating text with recurrent neural networks I Sutskever, J Martens, GE Hinton Proceedings of the 28th international conference on machine learning (ICML …, 2011 | 2011 | 2011 |
| Stochastic neighbor embedding GE Hinton, S Roweis Advances in neural information processing systems 15, 2002 | 2006 | 2002 |
| When does label smoothing help? R Müller, S Kornblith, GE Hinton Advances in neural information processing systems 32, 2019 | 1989 | 2019 |
Terrence SejnowskiFrancis Crick Professor, Salk Institute, Distingished Professor, UC San DiegoVerified email at salk.edu
