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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 371380 of 691 papers

TitleStatusHype
SGFormer: Simplifying and Empowering Transformers for Large-Graph RepresentationsCode2
MUBen: Benchmarking the Uncertainty of Molecular Representation ModelsCode0
Self-supervised Learning and Graph Classification under Heterophily0
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
MolCAP: Molecular Chemical reActivity pretraining and prompted-finetuning enhanced molecular representation learning0
Automated 3D Pre-Training for Molecular Property PredictionCode1
Efficient Approximations of Complete Interatomic Potentials for Crystal Property PredictionCode0
Simplicial Message Passing for Chemical Property Prediction0
CrysMMNet: Multimodal Representation for Crystal Property PredictionCode1
A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction0
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