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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 301–325 of 691 papers

TitleStatusHype
Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks—0
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing—0
EBSD Grain Knowledge Graph Representation Learning for Material Structure-Property Prediction—0
A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction—0
Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on Chemical Structure—0
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction—0
Molecule Design by Latent Prompt Transformer—0
Dual-Modality Representation Learning for Molecular Property Prediction—0
Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction—0
A molecular hypergraph convolutional network with functional group information—0
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information—0
Multi-View Graph Neural Networks for Molecular Property Prediction—0
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules—0
BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models—0
A Machine Learning Method for Material Property Prediction: Example Polymer Compatibility—0
Language model driven: a PROTAC generation pipeline with dual constraints of structure and property—0
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup—0
Enforcing Predictive Invariance across Structured Biomedical Domains—0
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures—0
A Comprehensive and Versatile Multimodal Deep Learning Approach for Predicting Diverse Properties of Advanced Materials—0
All You Need Is Synthetic Task Augmentation—0
A Structured Framework for Predicting Sustainable Aviation Fuel Properties using Liquid-Phase FTIR and Machine Learning—0
Language models in molecular discovery—0
Automatic Identification of Chemical Moieties—0
Distribution Learning for Molecular Regression—0
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