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MAVE: A Product Dataset for Multi-source Attribute Value Extraction


Dec 16, 2021
Li Yang, Qifan Wang, Zac Yu, Anand Kulkarni, Sumit Sanghai, Bin Shu, Jon Elsas, Bhargav Kanagal

* 10 pages, 7 figures. Accepted to WSDM 2022. Dataset available at https://github.com/google-research-datasets/MAVE 

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Machine Learning and Data Analytics for Design and Manufacturing of High-Entropy Materials Exhibiting Mechanical or Fatigue Properties of Interest


Dec 05, 2020
Baldur Steingrimsson, Xuesong Fan, Anand Kulkarni, Michael C. Gao, Peter K. Liaw

* Fundamental Studies in High-Entropy Materials. Publisher: Springer. Editors: Dr. Peter K. Liaw and Dr. James Brechtl. 2021 
* Machine learning, Data analytics, Material design, Additive manufacturing, High-entropy material, Statistical regression, Sequential learning, Bayesian inference, Feature selection, Data curation, Inverse design representation, Forward prediction, Backward prediction, Joint optimization, Physics-based modeling, Reinforcement learning, Statistical fatigue life model, Low-data environment 

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