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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 321330 of 691 papers

TitleStatusHype
Learning Hierarchical Interaction for Accurate Molecular Property PredictionCode0
Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal LearningCode0
Accelerating Material Property Prediction using Generically Complete Isometry InvariantsCode0
Improving Molecular Pretraining with Complementary FeaturizationsCode0
Graph Anisotropic DiffusionCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
Isotropic Gaussian Processes on Finite Spaces of GraphsCode0
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement LearningCode0
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation LearningCode0
Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE ModelCode0
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