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Deep neural networks have enabled progress in a wide variety of applications.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber · 2006
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Earlier work this paper cites.
Deep speech: Scaling up end-to-end speech recognition
A. Hannun, C. Case, J. Casper, B. Catanzaro, G. Diamos, E. Elsen, R. Prenger, S. Satheesh, S. Sengupta, A. Coates, et al · 2014
Earlier work this paper cites.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Binaryconnect: Training deep neural networks with binary weights during propagations
M. Courbariaux, Y. Bengio, and J.-P. David · 2015
Earlier work this paper cites.
Deep learning with limited numerical precision
S. Gupta, A. Agrawal, K. Gopalakrishnan, and P. Narayanan · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
Cited alongside, same era.
Faster R-CNN: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Cited alongside, same era.
Recurrent neural networks with limited numerical precision
J. Ott, Z. Lin, Y. Zhang, S.-C. Liu, and Y. Bengio · 2016
Later among the works it cites.
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks , pages 525–542
M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi · 2016
Later among the works it cites.
Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 2016
Later among the works it cites.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Y. Wu, M. Schuster, Z. Chen, Q. V. Le, M. Norouzi, W. Macherey, M. Krikun, Y. Cao, Q. Gao, K. Macherey, et al · 2016
Later among the works it cites.
Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
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C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
Cited alongside, same era.
Deep speech 2: End-to-end speech recognition in english and mandarin
D. Amodei, R. Anubhai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, J. Chen, M. Chrzanowski, A. Coates, G. Diamos, et al · 2016
Cited alongside, same era.
Exploring the limits of language modeling, 2016
R. Jozefowicz, O. Vinyals, M. Schuster, N. Shazeer, and Y. Wu · 2016
Cited alongside, same era.
Faster r-cnn github repository
R. Girshick
Cited in the paper.
Tensorflow tutorial: Sequence-to-sequence models
Cited in the paper.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun
Cited in the paper.
Identity mappings in deep residual networks
K. He, X. Zhang, S. Ren, and J. Sun
Cited in the paper.
S. Zhou, Z. Ni, X. Zhou, H. Wen, Y. Wu, and Y. Zou · 2016
Later among the works it cites.
Wrpn: Wide reduced-precision networks
A. Mishra, E. Nurvitadhi, J. Cook, and D. Marr · 2017
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Nvidia tesla v100 gpu architecture
NVIDIA · 2017
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Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
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