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SI data for paper "A delta-Machine Learning Approach to Improve the Quantum Chemistry Prediction of Solution-phase Molecular Properties at Ground and Excited States"

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SI_data_ml-representation_paper

SI data for paper "A delta-Machine Learning Approach to Improve the Quantum Chemistry Prediction of Solution-phase Molecular Properties at Ground and Excited States" Folder structure:

├── README.txt
├── load_script.py
├── ROAS.csv
├── ROAS_feature
│       └── ROAS_*.csv
├── ROAS_models
│       └── ROAS_*.pkl
├── OROP_feature
│       └── OROP_*.csv
├── OROP_models
│       └── OROP_*.pkl
├── OMROP_feature
│       └── OMROP_*.csv
├── OMROP_models
│       └── OMROP_*.pkl
└── ROAS_optxyz
        └── *.xyz

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SI data for paper "A delta-Machine Learning Approach to Improve the Quantum Chemistry Prediction of Solution-phase Molecular Properties at Ground and Excited States"

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