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Grace X Gu

Showing results (1-10 of 32) with videos related to

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Nanotechnology|November 5, 2019
Recovery from mechanical degradation of graphene by defect enlargementBowen Zheng, Grace X Gu
Nano-Micro Letters|June 17, 2021
Machine Learning-Based Detection of Graphene Defects with Atomic PrecisionBowen Zheng, Grace X Gu
Proceedings of the National Academy of Sciences of the United States of America|July 30, 2021
Learning hidden elasticity with deep neural networksChun-Teh Chen, Grace X Gu
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|March 11, 2020
Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active LearningChun-Teh Chen, Grace X Gu
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|April 24, 2023
Physics-Informed Deep-Learning For Elasticity: Forward, Inverse, and Mixed ProblemsChun-Teh Chen, Grace X Gu
Nature Computational Science|August 27, 2024
Computational challenges in additive manufacturing for metamaterials designKeith A Brown, Grace X Gu
Nanomaterials (Basel, Switzerland)|September 28, 2021
Scalable Graphene Defect Prediction Using Transferable LearningBowen Zheng, Zeyu Zheng, Grace X Gu
Materials Horizons|February 9, 2022
Generative machine learning algorithm for lattice structures with superior mechanical propertiesSangryun Lee, Zhizhou Zhang, Grace X Gu
Bioinspiration & Biomimetics|November 28, 2019
Algorithmic-driven design of shark denticle bioinspired structures for superior aerodynamic propertiesJoshua Ott, Manuel Lazalde, Grace X Gu
ACS Applied Materials & Interfaces|April 27, 2023
Deep Learning Accelerated Design of Mechanically Efficient Architected MaterialsSangryun Lee, Zhizhou Zhang, Grace X Gu
Pageof 4

Showing results (1-10 of 32) with videos related to

Sort By:
Pageof 4
Nanotechnology|November 5, 2019
Recovery from mechanical degradation of graphene by defect enlargementBowen Zheng, Grace X Gu
Nano-Micro Letters|June 17, 2021
Machine Learning-Based Detection of Graphene Defects with Atomic PrecisionBowen Zheng, Grace X Gu
Proceedings of the National Academy of Sciences of the United States of America|July 30, 2021
Learning hidden elasticity with deep neural networksChun-Teh Chen, Grace X Gu
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|March 11, 2020
Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active LearningChun-Teh Chen, Grace X Gu
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|April 24, 2023
Physics-Informed Deep-Learning For Elasticity: Forward, Inverse, and Mixed ProblemsChun-Teh Chen, Grace X Gu
Nature Computational Science|August 27, 2024
Computational challenges in additive manufacturing for metamaterials designKeith A Brown, Grace X Gu
Nanomaterials (Basel, Switzerland)|September 28, 2021
Scalable Graphene Defect Prediction Using Transferable LearningBowen Zheng, Zeyu Zheng, Grace X Gu
Materials Horizons|February 9, 2022
Generative machine learning algorithm for lattice structures with superior mechanical propertiesSangryun Lee, Zhizhou Zhang, Grace X Gu
Bioinspiration & Biomimetics|November 28, 2019
Algorithmic-driven design of shark denticle bioinspired structures for superior aerodynamic propertiesJoshua Ott, Manuel Lazalde, Grace X Gu
ACS Applied Materials & Interfaces|April 27, 2023
Deep Learning Accelerated Design of Mechanically Efficient Architected MaterialsSangryun Lee, Zhizhou Zhang, Grace X Gu
Pageof 4