4 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
StormNet: Improving storm surge predictions with a GNN-based spatio-temporal offset forecasting model
Noujoud Nader, Stefanos Giaremis, Clint Dawson +3
Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent trends of rapid intensification an…
HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks
Noujoud Nadera, Hadi Majed, Stefanos Giaremis +4
The coastal regions of the eastern and southern United States are impacted by severe storm events, leading to significant loss of life and properties. Accurately forecasting storm…
Topological derivative approach for deep neural network architecture adaptation
C G Krishnanunni, Tan Bui-Thanh, Clint Dawson
This work presents a novel algorithm for progressively adapting neural network architecture along the depth. In particular, we attempt to address the following questions in a mathe…
TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems
Hai V. Nguyen, Tan Bui-Thanh, Clint Dawson
Efficient real-time solvers for forward and inverse problems are essential in engineering and science applications. Machine learning surrogate models have emerged as promising alte…
Storm Surge Modeling in the AI ERA: Using LSTM-based Machine Learning for Enhancing Forecasting Accuracy
Stefanos Giaremis, Noujoud Nader, Clint Dawson +3
Physics simulation results of natural processes usually do not fully capture the real world. This is caused for instance by limits in what physical processes are simulated and to w…