most citedUncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

math.NA2025

Approximating Young Measures With Deep Neural Networks

Rayehe Karimi Mahabadi, Jianfeng Lu, Hossein Salahshoor

Parametrized measures (or Young measures) enable to reformulate non-convex variational problems as convex problems at the cost of enlarging the search space from space of functions…

cs.SD2023★ 1 cited

Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties

Han Zhang, Rayehe Karimi Mahabadi, Cynthia Rudin +2

This paper studies the utility of techniques within uncertainty quantification, namely spectral projection and polynomial chaos expansion, in reducing sampling needs for characteri…