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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 7180 of 691 papers

TitleStatusHype
A community-powered search of machine learning strategy space to find NMR property prediction modelsCode1
Automated 3D Pre-Training for Molecular Property PredictionCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
Contrastive Dual-Interaction Graph Neural Network for Molecular Property PredictionCode1
A graph representation of molecular ensembles for polymer property predictionCode1
AugLiChem: Data Augmentation Library of Chemical Structures for Machine LearningCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
Comparison of Atom Representations in Graph Neural Networks for Molecular Property PredictionCode1
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