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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 121130 of 691 papers

TitleStatusHype
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation ModelCode1
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property PredictionCode1
ParticleGrid: Enabling Deep Learning using 3D Representation of MaterialsCode1
Materials Property Prediction with Uncertainty Quantification: A Benchmark StudyCode1
MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property PredictionCode1
OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials ScienceCode1
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
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
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