most citedImproving Direct Physical Properties Prediction of Heterogeneous Materials from Imaging Data via Convolutional Neural Network and a Morphology-Aware Generative Model

5 citations · 5 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2018

One-Shot Generation of Near-Optimal Topology through Theory-Driven Machine Learning

Ruijin Cang, Hope Yao, Yi Ren

We introduce a theory-driven mechanism for learning a neural network model that performs generative topology design in one shot given a problem setting, circumventing the conventio…

physics.comp-ph2017★ 5 cited

Improving Direct Physical Properties Prediction of Heterogeneous Materials from Imaging Data via Convolutional Neural Network and a Morphology-Aware Generative Model

Ruijin Cang, Hechao Li, Hope Yao +2

Direct prediction of material properties from microstructures through statistical models has shown to be a potential approach to accelerating computational material design with lar…