recurrent_neural_network
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recurrent_neural_network [2020/10/22 02:24] 198.84.252.54 |
recurrent_neural_network [2022/06/15 02:27] burkov [Recommended Reading] |
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| * [[http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/|Implementing a GRU/LSTM RNN with Python and Theano]] by Denny Britz (2015) | * [[http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/|Implementing a GRU/LSTM RNN with Python and Theano]] by Denny Britz (2015) | ||
| * [[https://arxiv.org/abs/1701.03452|Simplified Minimal Gated Unit Variations for Recurrent Neural Networks]] by Joel Heck and Fathi Salem (2017) | * [[https://arxiv.org/abs/1701.03452|Simplified Minimal Gated Unit Variations for Recurrent Neural Networks]] by Joel Heck and Fathi Salem (2017) | ||
| - | * [[https://arxiv.org/abs/1706.03762|Attention Is All You Need]] by Vaswani et al. (2017), a state-of-the-art sequence-to-sequence model, plus an [[http://jalammar.github.io/illustrated-transformer/|illustrated guide]] | + | * [[https://arxiv.org/abs/1706.03762|Attention Is All You Need]] by Vaswani et al. (2017), a state-of-the-art sequence-to-sequence model, plus an [[http://jalammar.github.io/illustrated-transformer/|illustrated guide]] plus an [[http://nlp.seas.harvard.edu/annotated-transformer/|annotated paper with code]]. |
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