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Probabilistic Forecasting of Localized Wildfire Spread Based on Conditional Flow Matching
Bryan Shaddy, Haitong Qin, Brianna Binder +4
This study presents a probabilistic surrogate model for localized wildfire spread based on a conditional flow matching algorithm. The approach models fire progression as a stochast…
Generative Algorithms for Wildfire Progression Reconstruction from Multi-Modal Satellite Active Fire Measurements and Terrain Height
Bryan Shaddy, Brianna Binder, Agnimitra Dasgupta +8
Increasing wildfire occurrence has spurred growing interest in wildfire spread prediction. However, even the most complex wildfire models diverge from observed progression during m…
Unifying and extending Diffusion Models through PDEs for solving Inverse Problems
Agnimitra Dasgupta, Alexsander Marciano da Cunha, Ali Fardisi +4
Diffusion models have emerged as powerful generative tools with applications in computer vision and scientific machine learning (SciML), where they have been used to solve large-sc…
Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts
Bryan Shaddy, Deep Ray, Angel Farguell +7
Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in u…