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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

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Showing 441–450 of 691 papers

TitleStatusHype
Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal LearningCode0
Object-Centric Learning with Slot Mixture ModuleCode0
Identifying Semantic Component for Robust Molecular Property PredictionCode0
Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural NetworksCode0
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method—0
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent—0
Sliceformer: Make Multi-head Attention as Simple as Sorting in Discriminative TasksCode0
Unsupervised Learning of Molecular Embeddings for Enhanced Clustering and Emergent Properties for Chemical Compounds—0
Conformal Drug Property Prediction with Density Estimation under Covariate Shift—0
Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction—0
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