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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
141852012
Neural message passing for quantum chemistry
J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl
International conference on machine learning, 1263-1272, 2017
96642017
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
67152013
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
40872010
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
40862018
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
22852011
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
20532015
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
19412013
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
13982015
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
8032017
Deep belief networks for phone recognition
A Mohamed, G Dahl, G Hinton
NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 2009
6822009
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
6742017
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
6612013
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
5222018
Measuring the effects of data parallelism on neural network training
CJ Shallue, J Lee, J Antognini, J Sohl-Dickstein, R Frostig, GE Dahl
Journal of Machine Learning Research 20 (112), 1-49, 2019
4702019
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
4482010
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
4112011
On empirical comparisons of optimizers for deep learning
D Choi
arXiv preprint arXiv:1910.05446, 2019
4092019
Multi-task neural networks for QSAR predictions
GE Dahl, N Jaitly, R Salakhutdinov
arXiv preprint arXiv:1406.1231, 2014
4082014
Artificial intelligence–based breast cancer nodal metastasis detection: insights into the black box for pathologists
Y Liu, T Kohlberger, M Norouzi, GE Dahl, JL Smith, A Mohtashamian, ...
Archives of pathology & laboratory medicine 143 (7), 859-868, 2019
4012019
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