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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 151160 of 691 papers

TitleStatusHype
Improving Molecular Representation Learning with Metric Learning-enhanced Optimal TransportCode1
Graph Self-supervised Learning with Accurate Discrepancy LearningCode1
Regression Transformer: Concurrent sequence regression and generation for molecular language modelingCode1
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative GamesCode1
Improving VAE based molecular representations for compound property predictionCode1
Pairwise Learning for Neural Link PredictionCode1
Molecular Contrastive Learning with Chemical Element Knowledge GraphCode1
AugLiChem: Data Augmentation Library of Chemical Structures for Machine LearningCode1
Multiset-Equivariant Set Prediction with Approximate Implicit DifferentiationCode1
Geometric Transformer for End-to-End Molecule Properties PredictionCode1
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