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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 211220 of 691 papers

TitleStatusHype
MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding AnalysisCode0
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling PerspectiveCode0
Molecule Property Prediction and Classification with Graph HypernetworksCode0
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small ModelsCode0
Molecular Graph Representation Learning via Structural Similarity InformationCode0
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer GenerationCode0
Coarse-Grained Configurational Polymer Fingerprints for Property Prediction using Machine LearningCode0
Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profilesCode0
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation LearningCode0
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic ScreeningCode0
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