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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 321–330 of 691 papers

TitleStatusHype
All You Need Is Synthetic Task Augmentation—0
A Structured Framework for Predicting Sustainable Aviation Fuel Properties using Liquid-Phase FTIR and Machine Learning—0
Latent Tree Decomposition Parsers for AMR-to-Text Generation—0
Automatic Identification of Chemical Moieties—0
Distribution Learning for Molecular Regression—0
All SMILES Variational Autoencoder for Molecular Property Prediction and Optimization—0
In-Context Learning for Few-Shot Molecular Property Prediction—0
Discriminative protein sequence modelling with Latent Space Diffusion—0
Directional Message Passing on Molecular Graphs via Synthetic Coordinates—0
AlloyBERT: Alloy Property Prediction with Large Language Models—0
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