From the 1 of 12 linked papers with an AI index.
16 citations · 18 across the 5 of their papers we have counts for
8 papers · 1 filter
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates
Qiyao Zhou, Xujia Zhu, Pierre Joli +2
Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informative for parameter calibrati…
From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
Abhishek A. Sabnis, Mihai Mitrea, Lya Lugon +5
Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the complex interactions among poll…
A Probabilistic Approach to Wildfire Spread Prediction Using a Denoising Diffusion Surrogate Model
Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn +3
Thanks to recent advances in generative AI, computers can now simulate realistic and complex natural processes. We apply this capability to predict how wildfires spread, a task mad…
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data
Bo Pang, Sibo Cheng, Yuhan Huang +5
Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexi…
Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraint
Hanyang Wang, Hao Zhou, Sibo Cheng
Despite the success of various methods in addressing the issue of spatial reconstruction of dynamical systems with sparse observations, spatio-temporal prediction for sparse fields…
Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
Sibo Cheng, Hector Chassagnon, Matthew Kasoar +2
Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emis…