GitHub

NeuralChat — Seq2Seq LSTM Chatbot

Best GitHub Description: A production-ready conversational AI chatbot built from scratch using an Encoder–Decoder LSTM (Seq2Seq) architecture with teacher forcing, trained on the Cornell Movie Dialogs ...
GitHub

Core Module in my FInal Year Project: a sequence-to-sequence (Seq2Seq) encoder-decoder model using LSTM layers for abstractive text summarization

This repository contains the implementation of a Sequence-to-Sequence (Seq2Seq) Encoder-Decoder model for abstractive text summarization. It is developed using Bi-directional LSTM for the encoder and ...
IEEE

Attentional Seq2Seq Encoder-Decoder and Next Generation Reservoir Computing for Heartbeat Classification

Abstract: Cardiac dysfunctions are a global concern due to the high number of deaths it causes worldwide, as noted by the World Health Organization. The electrocardiogram signal is renowned for its ...
Your Story

Unlocking Seq2Seq Models: Mastering Variable-Length Sequences

Sequence-to-Sequence (Seq2Seq) models have revolutionised the field of natural language processing and machine translation. These models have the remarkable capability to handle both input and output ...
IEEE

SEMD: An Attention-Enhanced Multi-Decoder Seq2Seq for Direct Multi-Step Wind Power Forecasting

Abstract: Accurate multi-horizon wind power forecasting is essential for secure and economical power-system operation. To achieve this goal, we propose a Single-Encoder Multi-Decoder (SEMD) ...