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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 591600 of 691 papers

TitleStatusHype
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
Multipath Graph Convolutional Neural NetworksCode0
Ranking Structured Objects with Graph Neural NetworksCode0
MEG: Generating Molecular Counterfactual Explanations for Deep Graph NetworksCode1
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction0
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
Knowledge-aware Contrastive Molecular Graph Learning0
Molecular Representation Learning by Leveraging Chemical Information0
Structure-Enhanced Meta-Learning For Few-Shot Graph ClassificationCode0
Assigning Confidence to Molecular Property PredictionCode1
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