34 citations · 244 across the 35 of their papers we have counts for
35 papers
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…
A New Paradigm for 3D Turbomachinery Design: Generative Diffusion Model Based Framework with Direct Geometry Encoding
Yingfan Geng, Jinhong Wang, Lazaros Papachristodoulou +2
The aerodynamic design of turbomachinery is critical to the performance of the overall energy system, yet it is challenging due to the complex non-linear flow physics and the prese…
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…
Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
Zeyu Xia, Kan Ma, Sibo Cheng +7
The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcing phases. Chromium-based sup…
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…