The Decoder_Encoder_Model contains codes for building a neural encoder-decoder framework, which estimates the underlying cogntive state using behavioral readout and neural features.

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

We note that our work focuses on architectural comparisons rather than competing with recent SLM developments (e.g., SmolLM, MobileLLM). Our analysis isolates the fundamental advantages of ...

In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Encoder-decoder networks have become the standard solution for a variety of segmentation tasks. Many of these approaches use a symmetrical design where both the encoder as well as the decoder are ...

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

Discover the key differences between Moshi and Whisper speech-to-text models. Speed, accuracy, and use cases explained for your next project.

February 6, 2023 - Global IP Core Sales - The new DVB-RCS2 Turbo Encoder and Decoder IP Core is on the transmitter side, the turbo-phi encoder architecture is based on a parallel concatenation of two ...