An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another.

In machine translation, encoders generally encode words and phrases as internal representations the decoder then uses to generate text in a desired language.

Seq2Seq is essentially an abstract deion of a class of problems, rather than a specific model architecture, just as the ...

The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.

The technology to decode our thoughts is drawing ever closer. Neuroscientists at the University of Texas have for the first time decoded data from non-invasive brain scans and used them to reconstruct ...