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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

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Showing 431–440 of 691 papers

TitleStatusHype
Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems—0
Deep Learning based Dimple Segmentation for Quantitative Fractography—0
Deep Learning for Computational Chemistry—0
Deep Learning Methods for Small Molecule Drug Discovery: A Survey—0
Deep Robust Subjective Visual Property Prediction in Crowdsourcing—0
A General Approach for Determining Applicability Domain of Machine Learning Models—0
Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing—0
Directed Graph Attention Neural Network Utilizing 3D Coordinates for Molecular Property Prediction—0
Directional Message Passing on Molecular Graphs via Synthetic Coordinates—0
Discriminative protein sequence modelling with Latent Space Diffusion—0
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