Are they text, speech, images, or something else ... Choosing the best encoder-decoder architecture for your seq2seq model is not a trivial task. It depends on many factors, such as the input ...

The data needs some cleaning before being used to train our neural translation model. I implement encoder-decoder based seq2seq models with attention. The encoder and the decoder are pre-attention and ...

The objective of this project is to train a seq2seq model (an encoder-decoder model with attention) for machine translation. This project is motivated by the idea of implementing an advanced ...

An encoder-decoder (Seq2Seq) model is used for sentiment analysis of text. By adding character-level embedding to the word embedding layer, the OOV problem of pre-trained word vectors is solved. At ...

This work proposes two deep learning-based encoder-decoder models that automatically generate HTML (Hypertext Markup Language) code from screenshot images of web pages and hand-drawn sketches. The ...