thesfinox/ml-cicy
Machine Learning for CICY 3-folds
This project helps string theorists and mathematical physicists predict Hodge numbers for Complete Intersection Calabi-Yau 3-folds. It takes configuration matrices of CICY manifolds as input and outputs highly accurate predictions of their Hodge numbers. It is designed for researchers in string theory and related fields who work with complex manifold data.
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Use this if you need to predict Hodge numbers of CICY 3-folds using machine learning, especially if you are working with large datasets of manifold configuration matrices.
Not ideal if you are looking for a general-purpose machine learning tool outside the domain of string theory or if your primary interest is not in predicting Calabi-Yau manifold properties.
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Jan 03, 2021
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