18 citations · 24 across the 8 of their papers we have counts for
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math.NA2023★ 2 cited
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel
Moaad Khamlich, Federico Pichi, Gianluigi Rozza
Reduced order models (ROMs) are widely used in scientific computing to tackle high-dimensional systems. However, traditional ROM methods may only partially capture the intrinsic ge…
math.NA2023★ 2 cited
A physics-based reduced order model for urban air pollution prediction
Moaad Khamlich, Giovanni Stabile, Gianluigi Rozza +2
This article presents an innovative approach for developing an efficient reduced-order model to study the dispersion of urban air pollutants. The need for real-time air quality mon…