sergio94al/Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation
Registered Software. Official code of the published article "Automatic design of quantum feature maps". This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for tabular data.
This project helps quantum machine learning researchers and practitioners automatically design optimal quantum-inspired classifiers for tabular datasets. It takes classical tabular data as input and outputs highly accurate, compact quantum circuit designs. Researchers and quantum machine learning engineers developing or applying quantum classification models will find this useful.
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Use this if you need to efficiently generate specialized quantum-inspired classifiers that balance accuracy with circuit simplicity for your tabular data classification tasks.
Not ideal if your primary goal is to run computations on a physical quantum computer or if you are working with non-tabular data types like images or text.
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Mar 18, 2024
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