most citedA fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

208 citations · 240 across the 2 of their papers we have counts for

collaborators

2 papers

math.NA2020★ 32 cited

Efficient nonlinear manifold reduced order model

Youngkyu Kim, Youngsoo Choi, David Widemann +1

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations, in which the intrinsic solution space falls into a subspace with a small dim…

math.NA2020★ 208 cited

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

Youngkyu Kim, Youngsoo Choi, David Widemann +1

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations, in which the intrinsic solution space falls into a subspace with a small dim…