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Phys.org

Interpretable AI in materials discovery: Uncovering how models make predictions

Interpretable AI in materials discovery: Uncovering how models make predictions
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A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features from an AI model trained on atomic structural data and optical absorption spectra, and then groups materials with similar structural and spectral characteristics. This approach can be extended to rev

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