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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

Showing 581590 of 691 papers

TitleStatusHype
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer GenerationCode0
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property PredictionCode0
MatMMFuse: Multi-Modal Fusion model for Material Property PredictionCode0
Molecule Property Prediction and Classification with Graph HypernetworksCode0
Molecule Property Prediction Based on Spatial Graph EmbeddingCode0
Efficient Approximations of Complete Interatomic Potentials for Crystal Property PredictionCode0
The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMACode0
Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptorsCode0
Visualizing the Obvious: A Concreteness-based Ensemble Model for Noun Property PredictionCode0
DScribe: Library of Descriptors for Machine Learning in Materials ScienceCode0
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