1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CE2026
Aerodynamic Shape Design Space Exploration with Deep Latent Diffusion Model
Zhen Wei, Edouard Dufour, Colin Pelletier +2
We propose DiffGeo, a latent space diffusion-based generative framework for aerodynamic design space exploration under extreme data scarcity. DiffGeo combines a learned latent spac…
stat.ML2025
Do you understand epistemic uncertainty? Think again! Rigorous frequentist epistemic uncertainty estimation in regression
Enrico Foglia, Benjamin Bobbia, Nikita Durasov +4
Quantifying model uncertainty is critical for understanding prediction reliability, yet distinguishing between aleatoric and epistemic uncertainty remains challenging. We extend re…
cs.CV2023★ 1 cited
Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning
Zhen Wei, Pascal Fua, Michaël Bauerheim
We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric lear…