“We don’t break up image generation and text generation. We want it all to be done together.” Traditionally, A.I. image generators have struggled to create images that were markedly ...

While they may struggle with understanding complex input structures or relationships, as encoder-decoder models do, they are highly capable of generating fluent text. This makes them particularly good ...

The original transformer architecture consists of two main components: an encoder ... text generation, can be framed as autoregressive problems, where the model generates one token at a time, ...

On the one hand, the molecular features of the training set are stored in latent space by encoder, and on the other hand, these molecular features are reconstituted into new molecules by decoder ...

GANs consist of two main parts: the generator that generates data and the ... including translation, text summarization, and sentiment analysis. Encoder-decoder architectures are a broad category of ...

EnDeGen is a project that focuses on generating text using the Encoder-Decoder architecture with Recurrent Neural Networks (RNNs). It leverages the power of deep learning to predict and generate text ...