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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 251260 of 691 papers

TitleStatusHype
Molecular geometric deep learningCode0
Equivariant Message Passing Neural Network for Crystal Material DiscoveryCode0
Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable TargetsCode0
Molecular Graph Contrastive Learning with Line GraphCode0
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling PerspectiveCode0
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property PredictionCode0
Attentive Walk-Aggregating Graph Neural NetworksCode0
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific AdaptationCode0
Enhancing Molecular Property Prediction via Mixture of Collaborative ExpertsCode0
Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property PredictionCode0
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