Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning
Abstract In recent years, machine learning (ML) techniques are seen to be promising tools to discover and design novel materials. However, the lack of robust inverse design approaches to identify promising candidate materials without exploring the entire design space causes a fundamental bottleneck....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-03-01
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| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.201902607 |