Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study

By Abdelhafid Zeroual, Fouzi Harrou, Abdelkader Dairi, Ying Sun. Chaos, Solitons & Fractals, 2020

457 citations recorded by the source corpus.

Highlights • Developed deep learning methods to forecast the COVID19 spread.• Five deep learning models have been compared for COVID-19 forecasting.• Time-series COVID19 data from Italy, Spain, France, China, the USA, and Australia are used.• Results demonstrate the potential of deep learning models to forecast COVID19 data.• Results show the superior performance of the Variational AutoEncoder model.

Subfields: Artificial Intelligence, Modeling and Simulation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/e5f8648e788097923d789b7cfc44ed039f2523b4