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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 7180 of 691 papers

TitleStatusHype
ChemLLM: A Chemical Large Language ModelCode1
A graph representation of molecular ensembles for polymer property predictionCode1
ChiENN: Embracing Molecular Chirality with Graph Neural NetworksCode1
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property PredictionCode1
A community-powered search of machine learning strategy space to find NMR property prediction modelsCode1
AugLiChem: Data Augmentation Library of Chemical Structures for Machine LearningCode1
Explaining Deep Graph Networks with Molecular CounterfactualsCode1
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative GamesCode1
Chemical-Reaction-Aware Molecule Representation LearningCode1
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine LearningCode1
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