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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 451–460 of 691 papers

TitleStatusHype
In-Context Learning for Few-Shot Molecular Property Prediction—0
Splicing Up Your Predictions with RNA Contrastive LearningCode0
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction—0
Atom-Motif Contrastive Transformer for Molecular Property Prediction—0
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions—0
PointGAT: A quantum chemical property prediction model integrating graph attention and 3D geometry—0
Molecule Design by Latent Prompt Transformer—0
Towards out-of-distribution generalizable predictions of chemical kinetics propertiesCode0
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property PredictionCode0
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information—0
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