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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 2130 of 691 papers

TitleStatusHype
Generalizable, Fast, and Accurate DeepQSPR with fastpropCode2
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural NetworkCode2
Descriptor-based Foundation Models for Molecular Property PredictionCode2
Generative Artificial Intelligence for Navigating Synthesizable Chemical SpaceCode2
Analyzing Learned Molecular Representations for Property PredictionCode2
CrystalFormer-RL: Reinforcement Fine-Tuning for Materials DesignCode2
Deconstructing equivariant representations in molecular systemsCode2
SGFormer: Simplifying and Empowering Transformers for Large-Graph RepresentationsCode2
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, GeometryCode2
AstroCLIP: A Cross-Modal Foundation Model for GalaxiesCode1
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