118 citations · 145 across the 10 of their papers we have counts for
10 papers
A Data-Consistent Approach to Ensemble Filtering
Rylan Spence, Troy Butler, Clint Dawson
Ensemble data assimilation is challenging when the ensemble size is substantially smaller than the state and observation dimensions, leaving empirical covariance information rank d…
HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
Jinpai Zhao, Nishant Panda, Yen Ting Lin +3
We introduce HyCOP, a modular framework that learns parametric PDE solution operators by composing simple modules (advection, diffusion, learned closures, boundary handling) in a q…
Rapid Flood Inundation Forecast Using Fourier Neural Operator
Alexander Y. Sun, Zhi Li, Wonhyun Lee +3
Flood inundation forecast provides critical information for emergency planning before and during flood events. Real time flood inundation forecast tools are still lacking. High-res…
Parameter Estimation with Maximal Updated Densities
Michael Pilosov, Carlos del-Castillo-Negrete, Tian Yu Yen +2
A recently developed measure-theoretic framework solves a stochastic inverse problem (SIP) for models where uncertainties in model output data are predominantly due to aleatoric (i…
A Hybrid 2-stage Neural Optimization for Pareto Front Extraction
Gurpreet Singh, Soumyajit Gupta, Matthew Lease +1
Classification, recommendation, and ranking problems often involve competing goals with additional constraints (e.g., to satisfy fairness or diversity criteria). Such optimization…
SCA-Net: A Self-Correcting Two-Layer Autoencoder for Hyper-spectral Unmixing
Gurpreet Singh, Soumyajit Gupta, Clint Dawson
Hyperspectral unmixing involves separating a pixel as a weighted combination of its constituent endmembers and corresponding fractional abundances, with the current state of the ar…
Range-Net: A High Precision Streaming SVD for Big Data Applications
Gurpreet Singh, Soumyajit Gupta, Matthew Lease +1
In a Big Data setting computing the dominant SVD factors is restrictive due to the main memory requirements. Recently introduced streaming Randomized SVD schemes work under the res…
Prevention is Better than Cure: Handling Basis Collapse and Transparency in Dense Networks
Gurpreet Singh, Soumyajit Gupta, Clint N. Dawson
Dense nets are an integral part of any classification and regression problem. Recently, these networks have found a new application as solvers for known representations in various…
TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes
Gurpreet Singh, Soumyajit Gupta, Matt Lease +1
Partial Differential Equations are infinite dimensional encoded representations of physical processes. However, imbibing multiple observation data towards a coupled representation…
High Temporal Resolution Rainfall Runoff Modelling Using Long-Short-Term-Memory (LSTM) Networks
Wei Li, Amin Kiaghadi, Clint N. Dawson
Accurate and efficient models for rainfall runoff (RR) simulations are crucial for flood risk management. Most rainfall models in use today are process-driven; i.e. they solve eith…