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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 8190 of 691 papers

TitleStatusHype
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
A graph representation of molecular ensembles for polymer property predictionCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
Few-Shot Graph Learning for Molecular Property PredictionCode1
Can Large Language Models Understand Molecules?Code1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative GamesCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesCode1
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