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The Decade of Deep Learning
As the 2010’s draw to a close, it’s worth taking a look back at the monumental progress that has been made in Deep Learning in this decade.[1] Driven by the development of ever-more powerful comput
Christopher watkin
Lee sedol
Group normalization
Neural networks
Convolutional neural networks
Generative adversarial networks
Value network architectures source
Rectifier nonlinearities improve neural network acoustic models
Convolutional networks for large
Accurate deep network
Highway networks
Convolutional neural network
Network training
Sparse rectifier neural networks
Deep learning
Computer vision
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