Search Results for author:
Found 1 papers, 0 papers with code
Generative Network-Based Reduced-Order Model for Prediction, Data Assimilation and Uncertainty Quantification
The results show that the proposed GN-based ROM can efficiently quantify uncertainty and accurately match the measurements and the golden standard, using only a few unconditional simulations of the full-order numerical PDE model.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
