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Storm Surge Modeling in the AI ERA: Using LSTM-based Machine Learning for Enhancing Forecasting Accuracy
This is an important result that implies the possibility to apply a pre-trained ML model to real-time hurricane forecasting results with the goal of bias correcting and improving the produced simulation accuracy.
Rapid Flood Inundation Forecast Using Fourier Neural Operator
Flood inundation forecast provides critical information for emergency planning before and during flood events.
A Framework for Flexible Peak Storm Surge Prediction
Additionally, we propose a new formulation of the surrogate problem in which storm surge is predicted independently for each point.
SCA-Net: A Self-Correcting Two-Layer Autoencoder for Hyper-spectral Unmixing
We show for the first time that a two-layer autoencoder (SCA), with $2FK$ parameters ($F$ features, $K$ endmembers), achieves error metrics that are scales apart ($10^{-5})$ from previously reported values $(10^{-2})$.
A Hybrid 2-stage Neural Optimization for Pareto Front Extraction
The first stage (neural network) efficiently extracts a weak Pareto front, using Fritz-John conditions as the discriminator, with no assumptions of convexity on the objectives or constraints.
Range-Net: A High Precision Streaming SVD for Big Data Applications
Although these methods are claimed to be applicable to scientific computations due to associated tail-energy error bounds, the approximation errors in the singular vectors and values are high when the aforementioned assumption does not hold.
