Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators
cs.LG, physics.ao-ph, physics.comp-ph
Submitted: 2026-05-05
Updated: 2026-09-09
Comments: 28 pages, 9 figures
Code: https://github.com/wrf-model/WPS
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Verification and Validation for Trustworthy Scientific Machine Learning
- WRF fire simulation coupled with a fuel moisture model and smoke transport by WRF-Chem
- Improved Wildfire Spread Prediction with Time-Series Data and the WSTS+ Benchmark
- Neural Operator: Graph Kernel Network for Partial Differential Equations
- Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
- Nonlinear integro-differential operator regression with neural networks
- A Tutorial on Principal Component Analysis
- An Optimal Weighted Least-Squares Method for Operator Learning
- Performance of Neural and Polynomial Operator Surrogates
- Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems
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