George E. Dahl
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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
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
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
Neural message passing for quantum chemistry
J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl
International conference on machine learning, 1263-1272, 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
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
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
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
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
Deep belief networks for phone recognition
A Mohamed, G Dahl, G Hinton
NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 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
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
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
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
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
Multi-task neural networks for QSAR predictions
GE Dahl, N Jaitly, R Salakhutdinov
arXiv preprint arXiv:1406.1231, 2014
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
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
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
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
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