Search Results for author: Yabo Dan

Found 1 papers, 0 papers with code

Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials

no code implementations12 Nov 2019 Yabo Dan, Yong Zhao, Xiang Li, Shaobo Li, Ming Hu, Jianjun Hu

The percentage of chemically valid (charge neutral and electronegativity balanced) samples out of all generated ones reaches 84. 5% by our GAN when trained with materials from ICSD even though no such chemical rules are explicitly enforced in our GAN model, indicating its capability to learn implicit chemical composition rules.

Generative Adversarial Network valid

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