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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 611–620 of 691 papers

TitleStatusHype
Latent Tree Decomposition Parsers for AMR-to-Text Generation—0
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction—0
Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks—0
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation LearningCode0
On Graph Neural Network Ensembles for Large-Scale Molecular Property PredictionCode0
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction—0
Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech—0
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformationCode0
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction—0
MoleHD: Ultra-Low-Cost Drug Discovery using Hyperdimensional Computing—0
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