Active Learning for Materials Design with Kevin Tran - TWiML Talk #238
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Active Learning in Materials Design
This chapter explores the integration of active learning and machine learning in materials design through quantum mechanics-based simulations. It details the iterative process of predicting binding energies and characterizing materials, emphasizing the balance between exploration and exploitation for optimal candidate selection. The discussion highlights innovative data analysis methods and the collaborative efforts required for validating new materials in experimental settings.
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