IEEE

A Dual Output Temporal Convolutional Network With Attention Architecture for Stock Price Prediction and Risk Assessment

Abstract: In this paper, we propose a novel deep learning model that integrates a Temporal Convolutional Network (TCN) with an Attention mechanism to predict stock prices and assess risk for ...
IEEE

Deep Learning-Based PM2.5 Concentration Estimation Using Convolutional Neural Network on Environmental Image Data

Abstract: Globalization and rapid progress in technology is leading to the pollution of the environment severely affecting public health and leading to deaths. Air quality in most of the cities at ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...