Sequence to Sequence Learning with Neural Networks
4 stacked LSTM cells of 1000 hidden size with reversed input sentences, and with beam search, on the WMT’14 English to French dataset.
- from
- Education
- added
- 2026-10-10
- likes
- 0
similar
-
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation arxiv.org
Two networks in one combined into a seq2seq (sequence to sequence) Encoder-Decoder architecture. RNN Encoder–Decoder with 1000 hidden units. Adadelta optimizer.
-
Deep stacked residual bidirectional LSTMs for HAR github.com
Improvements on the previous project.
-
Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation arxiv.org
In 2016: stacked residual LSTMs with attention mechanisms on encoder/decoder are the best for NMT (Neural Machine Translation).
-
Sequence Learning using RNN (Slides) slideshare.net
-
An efficient, batched LSTM. gist.github.com
-
LSTM explained apaszke.github.io
Education › Papers > Recurrent Neural Networks: “4 stacked LSTM cells of 1000 hidden size with reversed input sentences, and with beam search, on the WMT’14 English to French dataset.”