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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 501–525 of 691 papers

TitleStatusHype
Set-based Meta-Interpolation for Few-Task Meta-Learning—0
A graph representation of molecular ensembles for polymer property predictionCode1
Partial Product Aware Machine Learning on DNA-Encoded Libraries—0
FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction—0
Transferring Chemical and Energetic Knowledge Between Molecular Systems with Machine Learning—0
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property PredictionCode1
Crystal Twins: Self-supervised Learning for Crystalline Material Property Prediction—0
Attention-wise masked graph contrastive learning for predicting molecular property—0
Graph Anisotropic DiffusionCode0
Learning to Split for Automatic Bias DetectionCode1
Infusing Linguistic Knowledge of SMILES into Chemical Language Models—0
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup—0
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications—0
Automatic Identification of Chemical Moieties—0
Protein Representation Learning by Geometric Structure PretrainingCode2
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptorsCode1
A Machine Learning Method for Material Property Prediction: Example Polymer Compatibility—0
Equilibrium Aggregation: Encoding Sets via Optimization—0
Addressing Over-Smoothing in Graph Neural Networks via Deep Supervision—0
Structured Multi-task Learning for Molecular Property PredictionCode1
Equivariant Graph Attention Networks for Molecular Property Prediction—0
Knowledge-informed Molecular Learning: A Survey on Paradigm Transfer—0
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug DiscoveryCode3
Improving Molecular Representation Learning with Metric Learning-enhanced Optimal TransportCode1
Graph Self-supervised Learning with Accurate Discrepancy LearningCode1
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