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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

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Showing 121–130 of 691 papers

TitleStatusHype
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
MD-HIT: Machine learning for materials property prediction with dataset redundancy controlCode1
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
Meta-Learning with Fewer Tasks through Task InterpolationCode1
ADMET property prediction through combinations of molecular fingerprintsCode1
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human LanguageCode1
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property PredictionCode1
Dual-view Molecule Pre-trainingCode1
E(n) Equivariant Topological Neural NetworksCode1
3DReact: Geometric deep learning for chemical reactionsCode1
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