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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 461470 of 691 papers

TitleStatusHype
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informaticsCode1
Unraveling Key Elements Underlying Molecular Property Prediction: A Systematic StudyCode1
Periodic Graph Transformers for Crystal Material Property PredictionCode1
Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties0
Artificial Intelligence in Material Engineering: A review on applications of AI in Material Engineering0
Graph Neural Networks for Molecules0
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients0
Uni-Mol: A Universal 3D Molecular Representation Learning Framework0
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters0
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