Search Results for author: Hope Yao

Found 2 papers, 2 papers with code

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

1 code implementation27 Jul 2018 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 conventional iterative process that computational design tasks usually entail.

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

1 code implementation7 Dec 2017 Ruijin Cang, Hechao Li, Hope Yao, Yang Jiao, Yi Ren

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

Computational Physics Materials Science

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