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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 126–150 of 691 papers

TitleStatusHype
OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials ScienceCode1
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informaticsCode1
Unraveling Key Elements Underlying Molecular Property Prediction: A Systematic StudyCode1
Periodic Graph Transformers for Crystal Material Property PredictionCode1
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural LanguageCode1
TransPolymer: a Transformer-based language model for polymer property predictionsCode1
HiGNN: Hierarchical Informative Graph Neural Networks for Molecular Property Prediction Equipped with Feature-Wise AttentionCode1
Semi-Supervised Junction Tree Variational Autoencoder for Molecular Property PredictionCode1
A Gaze into the Internal Logic of Graph Neural Networks, with LogicCode1
Deep learning-based denoising for fast time-resolved flame emission spectroscopy in high-pressure combustion environmentCode1
FunQG: Molecular Representation Learning Via Quotient GraphsCode1
Unified 2D and 3D Pre-Training of Molecular RepresentationsCode1
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture SearchCode1
Graph-based Molecular Representation LearningCode1
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide ElectrocatalystsCode1
LIMO: Latent Inceptionism for Targeted Molecule GenerationCode1
Graph Rationalization with Environment-based AugmentationsCode1
Shortest Path Networks for Graph Property PredictionCode1
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property PredictionCode1
Pre-training via Denoising for Molecular Property PredictionCode1
A graph representation of molecular ensembles for polymer property predictionCode1
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property PredictionCode1
Learning to Split for Automatic Bias DetectionCode1
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptorsCode1
Structured Multi-task Learning for Molecular Property PredictionCode1
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