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Check out some of the work done by our incredible minds based on science-driven AI
Explainable AI
Chemical hardness-driven interpretable machine learning approach for rapid search of photocatalysts. Intuitive Method of interpreting ‘black box’ models
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Physics Based Learning
Coupling the High-Throughput Property Map to Machine Learning for Predicting Lattice Thermal Conductivity. Physical connections between properties
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Structure-Property Linkages
Accelerated prediction of Vickers hardness of Co- and Ni-based superalloys from microstructure and composition using advanced image processing techniques and machine learning.
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Development of AI algorithms
Feature Blending: An Approach toward Generalized Machine Learning Models for Property Prediction.Capturing class-specific and global traits with ingenious blending of selected features
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