| 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 | 11315 | 2012 |
| 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 | 4561 | 2013 |
| Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl International conference on machine learning, 1263-1272, 2017 | 3797 | 2017 |
| Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition G Dahl, D Yu, L Deng, A Acero Audio, Speech, and Language Processing, IEEE Transactions on, 1-1, 2010 | 3424 | 2010 |
| Acoustic modeling using deep belief networks A Mohamed, GE Dahl, G Hinton IEEE transactions on audio, speech, and language processing 20 (1), 14-22, 2011 | 2008 | 2011 |
| Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 1997 | 2018 |
| Deep convolutional neural networks for large-scale speech tasks TN Sainath, B Kingsbury, G Saon, H Soltau, A Mohamed, G Dahl, ... Neural networks 64, 39-48, 2015 | 1713 | 2015 |
| Improving deep neural networks for LVCSR using rectified linear units and dropout GE Dahl, TN Sainath, GE Hinton 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 1598 | 2013 |
| Deep neural nets as a method for quantitative structure–activity relationships J Ma, RP Sheridan, A Liaw, GE Dahl, V Svetnik Journal of chemical information and modeling 55 (2), 263-274, 2015 | 884 | 2015 |
| Deep belief networks for phone recognition A Mohamed, G Dahl, G Hinton NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 2009 | 578 | 2009 |
| Detecting cancer metastases on gigapixel pathology images Y Liu, K Gadepalli, M Norouzi, GE Dahl, T Kohlberger, A Boyko, ... arXiv preprint arXiv:1703.02442, 2017 | 573 | 2017 |
| Large-scale malware classification using random projections and neural networks GE Dahl, JW Stokes, L Deng, D Yu 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 494 | 2013 |
| Prediction errors of molecular machine learning models lower than hybrid DFT error FA Faber, L Hutchison, B Huang, J Gilmer, SS Schoenholz, GE Dahl, ... Journal of chemical theory and computation 13 (11), 5255-5264, 2017 | 444 | 2017 |
| Phone recognition with the mean-covariance restricted Boltzmann machine G Dahl, MA Ranzato, A Mohamed, GE Hinton Advances in neural information processing systems 23, 2010 | 412 | 2010 |
| Deep belief networks using discriminative features for phone recognition A Mohamed, TN Sainath, G Dahl, B Ramabhadran, GE Hinton, ... 2011 IEEE international conference on acoustics, speech and signal …, 2011 | 384 | 2011 |
| Multi-task neural networks for QSAR predictions GE Dahl, N Jaitly, R Salakhutdinov arXiv preprint arXiv:1406.1231, 2014 | 308 | 2014 |
| Large scale distributed neural network training through online distillation R Anil, G Pereyra, A Passos, R Ormandi, GE Dahl, GE Hinton arXiv preprint arXiv:1804.03235, 2018 | 290 | 2018 |
| Measuring the effects of data parallelism on neural network training CJ Shallue, J Lee, J Antognini, J Sohl-Dickstein, R Frostig, GE Dahl arXiv preprint arXiv:1811.03600, 2018 | 246 | 2018 |
| Improvements to deep convolutional neural networks for LVCSR TN Sainath, B Kingsbury, A Mohamed, GE Dahl, G Saon, H Soltau, ... 2013 IEEE workshop on automatic speech recognition and understanding, 315-320, 2013 | 244 | 2013 |
| Large vocabulary continuous speech recognition with context-dependent DBN-HMMs GE Dahl, D Yu, L Deng, A Acero 2011 IEEE international conference on acoustics, speech and signal …, 2011 | 243 | 2011 |
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
