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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 181190 of 691 papers

TitleStatusHype
Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks0
GNN-SKAN: Harnessing the Power of SwallowKAN to Advance Molecular Representation Learning with GNNs0
A Structured Framework for Predicting Sustainable Aviation Fuel Properties using Liquid-Phase FTIR and Machine Learning0
Distribution Learning for Molecular Regression0
RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching0
Graph Residual based Method for Molecular Property Prediction0
Enhancing material property prediction with ensemble deep graph convolutional networks0
Guided Latent Slot Diffusion for Object-Centric Learning0
A Large Encoder-Decoder Family of Foundation Models For Chemical LanguageCode0
Scikit-fingerprints: easy and efficient computation of molecular fingerprints in PythonCode3
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