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Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases

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Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases

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Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Universal machine learning for the response of atomistic systems to external fields

Characterizing Conical Intersections in DNA/RNA Nucleobases with Multiconfigurational Wave Functions of Varying Active Space Size

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

Deterministic and Statistical Approaches to Quantum Chemistry

The ONETEP linear-scaling density functional theory program

Accurate molecular polarizabilities with coupled cluster theory and machine learning

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Characterizing Conical Intersections in DNA/RNA Nucleobases with Multiconfigurational Wave Functions of Varying Active Space Size

Universal machine learning for the response of atomistic systems to external fields

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Deterministic and Statistical Approaches to Quantum Chemistry

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

Accurate molecular polarizabilities with coupled cluster theory and machine learning

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The ONETEP linear-scaling density functional theory program