9 citations · 21 across the 8 of their papers we have counts for
3 papers · 1 filter
Shape Derivative-Informed Neural Operators with Application to Risk-Averse Shape Optimization
Xindi Gong, Dingcheng Luo, Thomas O'Leary-Roseberry +2
Shape optimization under uncertainty (OUU) is computationally intensive for classical PDE-based methods due to the high cost of repeated sampling-based risk evaluation across many…
Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators
Dingcheng Luo, Thomas O'Leary-Roseberry, Peng Chen +1
We propose a novel machine learning framework for solving optimization problems governed by large-scale partial differential equations (PDEs) with high-dimensional random parameter…
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm
Dingcheng Luo, Lianghao Cao, Peng Chen +2
Directed self-assembly (DSA) of block-copolymers (BCPs) is one of the most promising developments in the cost-effective production of nanoscale devices. The process makes use of th…