On Uncertainty Quantification in Materials Modeling and Discovery: Applications of GE's BHM and IDACE-Reference-Cited by-同舟云学术

On Uncertainty Quantification in Materials Modeling and Discovery: Applications of GE's BHM and IDACE

Published:2023-01-19 Issue: Volume: Page:
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Container-title:AIAA SCITECH 2023 Forum
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Author:

Ravi Sandipp Krishnan¹,Bhaduri Anindya¹,Amer Ahmad¹,Ghosh Sayan¹,Wang Liping¹,Hoffman Andrew¹,Umretiya Rajnikant¹,Roy Indranil¹,Rebak Raul¹,Dheeradhada Voramon S.¹,Ju Siyeong¹,Sun Changjie¹,Shower Patrick¹,Kebbede Anteneh¹,Kitt Alexander²,Kerwin Lee²,Mohr Luke²,Yuan Lang³,Feng Bojun¹,Roychowdhury Subhrajit¹

Affiliation:

1. GE Global Research

2. Edison Welding Institute

3. University of South Carolina

Publisher

American Institute of Aeronautics and Astronautics

Link

https://arc.aiaa.org/doi/pdf/10.2514/6.2023-0528

Reference52 articles.

1. Materials discovery and design using machine learning

2. Materials 4.0: Materials big data enabled materials discovery

3. Machine Learning in Materials Discovery: Confirmed Predictions and Their Underlying Approaches

4. Rethinking drug design in the artificial intelligence era

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