{"repo":"gonzalopezgil/xlstm-ts","free":true,"listed":false,"github":"https://github.com/gonzalopezgil/xlstm-ts","clone":"git clone https://github.com/gonzalopezgil/xlstm-ts.git","description":"Optimised Extended LSTM for time-series forecasting","language":"Jupyter Notebook","stars":47,"topics":["deep-learning","machine-learning","python","stock-market","time-series","wavelet-denoising","xlstm"],"license":"MIT","category":"machine-learning","readme_excerpt":"🚀 xLSTM-TS: Extended Long-Short Term Memory for Time Series Authors: Gonzalo López Gil, Paul Duhamel-Sebline, Andrew McCarren Published in: An Evaluation of Deep Learning Models for Stock Market Trend Prediction This repository contains the implementation of the xLSTM-TS model , a time series-optimised adaptation of the Extended Long Short-Term Memory (xLSTM) architecture proposed by Beck et al. (2024). The xLSTM-TS model modifies the xLSTM framework to make it suitable for time series forecasting. The architecture includes the xLSTM-TS implementation and integrates wavelet denoising techniques to enhance forecasting accuracy. While designed for versatility in time series forecasting, the model has been applied to short-term Stock Market Trend Prediction, demonstrating its effectiveness in financial applications as a key use case. In addition to xLSTM-TS, this repository features implementations of several state-of-the-art forecasting models for benchmarking purposes, such as TCN, N-BEATS, TFT, N-HiTS, and TiDE. These models have been evaluated alongside xLSTM-TS in our study. This repository provides datasets and code for the complete workflow, from preprocessing, to model training, and evaluation, along with detailed comparisons of accuracy and trend prediction capabilities. This is the official repository for the paper \"An Evaluation of Deep Learning Models for Stock Market Trend Prediction.\" 📋 Table of Contents - ✨ Key Features - 📄 Abstract - ⚙️ Installation - 🚀 Usage","default_branch":null,"files":null,"tree":[],"storefront":"/r/gonzalopezgil","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/gonzalopezgil/xlstm-ts/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}