PyQAlloy is a tool for detection of abnormal data in alloy datasets (and other chemical spaces), allowing removal of hard-to-find erros in the data which often introduce systematic errors throwing off machine learning and researchers alike. Its development is a part of ULTERA Project carried under the DOE ARPA-E ULTIMATE program that aims to develop a new generation of materials for turbine blades and related applications.
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Summary
PyQAlloy is a tool for detection of abnormal data in alloy datasets (and other chemical spaces), allowing removal of hard-to-find erros in the data which often introduce systematic errors throwing off machine learning and researchers alike. Its development is a part of ULTERA Project carried under the DOE ARPA-E ULTIMATE program that aims to develop a new generation of materials for turbine blades and related applications.
Last Updated
Jan 8, 2025 at 18:01
License
MIT
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