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Property Prediction

Property prediction involves forecasting or estimating a molecule's inherent physical and chemical properties based on information derived from its structural characteristics. It facilitates high-throughput evaluation of an extensive array of molecular properties, enabling the virtual screening of compounds. Additionally, it provides the means to predict the unknown attributes of new molecules, thereby bolstering research efficiency and reducing development times.

Papers

Showing 6170 of 691 papers

TitleStatusHype
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
ADMET property prediction through combinations of molecular fingerprintsCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
Chemical-Reaction-Aware Molecule Representation LearningCode1
Equivariance Everywhere All At Once: A Recipe for Graph Foundation ModelsCode1
Few-Shot Graph Learning for Molecular Property PredictionCode1
Bayesian Graph Neural Networks for Molecular Property PredictionCode1
A community-powered search of machine learning strategy space to find NMR property prediction modelsCode1
E(n) Equivariant Topological Neural NetworksCode1
A graph representation of molecular ensembles for polymer property predictionCode1
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