4 citations · 5 across the 4 of their papers we have counts for
4 papers
A Multi-Fidelity Graph U-Net Model for Accelerated Physics Simulations
Rini Jasmine Gladstone, Hadi Meidani
Physics-based deep learning frameworks have shown to be effective in accurately modeling the dynamics of complex physical systems with generalization capability across problem inpu…
Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment
Tong Liu, Hadi Meidani
Traffic assignment and traffic flow prediction provide critical insights for urban planning, traffic management, and the development of intelligent transportation systems. An effic…
Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction
Weiheng Zhong, Hadi Meidani, Jane Macfarlane
Traffic forecasting is an important issue in intelligent traffic systems (ITS). Graph neural networks (GNNs) are effective deep learning models to capture the complex spatio-tempor…
GNN-based physics solver for time-independent PDEs
Rini Jasmine Gladstone, Helia Rahmani, Vishvas Suryakumar +3
Physics-based deep learning frameworks have shown to be effective in accurately modeling the dynamics of complex physical systems with generalization capability across problem inpu…