Analytics India Magazine

Using Encoder-Decoder LSTM in Univariate Horizon Style for Time Series Modelling

In machine learning, we have seen various kinds of neural networks and encoder-decoder models are also a type of neural network in which recurrent neural networks are used to make the prediction on ...
inc42

What Is Encoder-Decoder Architecture? Here’s All You Need to Know

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...
GitHub

understanding-of-LLM-Encoder-and-decoder-model-

An Encoder-Decoder model is a fundamental architecture in the field of deep learning and natural language processing (NLP). It's widely used for a variety of tasks, including machine translation, text ...
GitHub

Swift BPE Encoder/Decoder for OpenAI GPT Models. A programmatic interface for tokenizing text for OpenAI GPT API.

The GPT family of models process text using tokens, which are common sequences of characters found in text. The models understand the statistical relationships between these tokens, and excel at ...
Microsoft

A Unified Encoder-Decoder Framework with Entity Memory

Entities, as important carriers of real-world knowledge, play a key role in many NLP tasks. We focus on incorporating entity knowledge into an encoder-decoder framework for informative text generation ...
IEEE

ESNet: Anti-Hierarchical Encoder–Decoder Network With Surrounding Expansion and Stripping for Hyperspectral Image Classification

Abstract: Spatial information is crucial in deep spectral–spatial hyperspectral image (HSI) classification methods. Spatial features can be divided into central features and surrounding features, ...
IEEE

Encoder-Decoder Based Attractors for End-to-End Neural Diarization

Abstract: This paper investigates an end-to-end neural diarization (EEND) method for an unknown number of speakers. In contrast to the conventional cascaded approach to speaker diarization, EEND ...