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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 171180 of 691 papers

TitleStatusHype
Hierarchical graph neural nets can capture long-range interactionsCode1
Generalization and Robustness Implications in Object-Centric LearningCode1
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property PredictionCode1
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life ScienceCode1
Dual-view Molecule Pre-trainingCode1
Fast Quantum Property Prediction via Deeper 2D and 3D Graph NetworksCode1
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
Meta-Learning with Fewer Tasks through Task InterpolationCode1
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