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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 341350 of 691 papers

TitleStatusHype
Interpretation of Semantic Tweet RepresentationsCode0
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph LearningCode0
Visualizing the Obvious: A Concreteness-based Ensemble Model for Noun Property PredictionCode0
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction TasksCode0
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged ZeolitesCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Molecular Joint Representation Learning via Multi-modal Information0
Machine Learning Models for Accurately Predicting Properties of CsPbCl3 Perovskite Quantum Dots0
GNN-SKAN: Harnessing the Power of SwallowKAN to Advance Molecular Representation Learning with GNNs0
MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction0
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