20 citations · 39 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 19 cited
Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations
César Quilodrán-Casas, Rossella Arcucci, Laetitia Mottet +2
This paper presents an approach to improve the forecast of computational fluid dynamics (CFD) simulations of urban air pollution using deep learning, and most specifically adversar…
cs.LG2020★ 20 cited
Data Assimilation in the Latent Space of a Neural Network
Maddalena Amendola, Rossella Arcucci, Laetitia Mottet +5
There is an urgent need to build models to tackle Indoor Air Quality issue. Since the model should be accurate and fast, Reduced Order Modelling technique is used to reduce the dim…