| 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 | 9507 | 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 | 3469 | 2013 |
| 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 | 3079 | 2010 |
| Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl International Conference on Machine Learning, 1263-1272, 2017 | 1941 | 2017 |
| 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 | 1851 | 2011 |
| 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 | 1309 | 2013 |
| 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 | 1129 | 2018 |
| 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 | 668 | 2015 |
| Deep belief networks for phone recognition A Mohamed, G Dahl, G Hinton Nips workshop on deep learning for speech recognition and related …, 2009 | 520 | 2009 |
| Deep belief networks for phone recognition A Mohamed, G Dahl, G Hinton NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 2009 | 520 | 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 | 431 | 2017 |
| 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 | 414 | 2015 |
| 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 | 403 | 2013 |
| Phone recognition with the mean-covariance restricted Boltzmann machine G Dahl, MA Ranzato, A Mohamed, GE Hinton Advances in neural information processing systems 23, 469-477, 2010 | 387 | 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 | 352 | 2011 |
| 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 | 334 | 2017 |
| Multi-task neural networks for QSAR predictions GE Dahl, N Jaitly, R Salakhutdinov arXiv preprint arXiv:1406.1231, 2014 | 247 | 2014 |
| rahman Mohamed G Hinton, L Deng, D Yu, G Dahl A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T., and …, 2012 | 247 | 2012 |
| 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 | 222 | 2011 |
| Roles of pre-training and fine-tuning in context-dependent DBN-HMMs for real-world speech recognition D Yu, L Deng, G Dahl Proc. NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 2010 | 215 | 2010 |
Dong Yu (俞栋)Distinguished Scientist and Vice General Manager, Tencent AI LabVerified email at tencent.com
