Adversarially trained LSTMs on reduced order models of urban air pollution simulations

5 January 2021

Papers citing "Adversarially trained LSTMs on reduced order models of urban air pollution simulations"

4 / 4 papers shown

Title
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 32 124 0 18 Mar 2023
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes C. Heaney Zef Wolffs Jón Atli Tómasson L. Kahouadji P. Salinas A. Nicolle Omar K. Matar Ionel M. Navon N. Srinil Christopher C. Pain AI4CE 24 21 0 13 Feb 2022
Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations César Quilodrán-Casas Rossella Arcucci Laetitia Mottet Yike Guo Christopher C. Pain AI4CE 17 8 0 13 Apr 2021
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic César Quilodrán-Casas Vinicius L. S. Silva Rossella Arcucci C. Heaney Yike Guo Christopher C. Pain 26 40 0 03 Feb 2021