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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 1120 of 691 papers

TitleStatusHype
Descriptor-based Foundation Models for Molecular Property PredictionCode2
CrystalFormer-RL: Reinforcement Fine-Tuning for Materials DesignCode2
M^3-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and DiscoveryCode2
Deconstructing equivariant representations in molecular systemsCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
ProtT3: Protein-to-Text Generation for Text-based Protein UnderstandingCode2
Generalizable, Fast, and Accurate DeepQSPR with fastpropCode2
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph TransformersCode2
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, GeometryCode2
Improving Molecular Properties Prediction Through Latent Space FusionCode2
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