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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 101110 of 691 papers

TitleStatusHype
A new perspective on building efficient and expressive 3D equivariant graph neural networksCode1
Heterogenous Ensemble of Models for Molecular Property PredictionCode1
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine LearningCode1
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text ModelingCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
Chemical-Reaction-Aware Molecule Representation LearningCode1
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life ScienceCode1
ChemLLM: A Chemical Large Language ModelCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human LanguageCode1
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