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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 51–75 of 691 papers

TitleStatusHype
3DReact: Geometric deep learning for chemical reactionsCode1
Automated 3D Pre-Training for Molecular Property PredictionCode1
Multi-channel learning for integrating structural hierarchies into context-dependent molecular representationCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
Bayesian Graph Neural Networks for Molecular Property PredictionCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
Dynamic In-context Learning with Conversational Models for Data Extraction and Materials Property PredictionCode1
E(n) Equivariant Topological Neural NetworksCode1
Equivariance Everywhere All At Once: A Recipe for Graph Foundation ModelsCode1
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property PredictionCode1
Artificial Intelligence in Drug Discovery: Applications and TechniquesCode1
ADMET property prediction through combinations of molecular fingerprintsCode1
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life ScienceCode1
Directed Graph Grammars for Sequence-based LearningCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and moleculesCode1
Dual-view Molecule Pre-trainingCode1
Explaining Deep Graph Networks with Molecular CounterfactualsCode1
A community-powered search of machine learning strategy space to find NMR property prediction modelsCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
A graph representation of molecular ensembles for polymer property predictionCode1
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materialsCode1
Comparison of Atom Representations in Graph Neural Networks for Molecular Property PredictionCode1
Contrastive Dual-Interaction Graph Neural Network for Molecular Property PredictionCode1
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