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Predicting molecular properties with covariant compositional networks

The Journal of Chemical Physics, 2018
Density functional theory (DFT) is the most successful and widely used approach for computing the electronic structure of matter. However, for tasks involving large sets of candidate molecules, running DFT separately for every possible compound of interest is forbiddingly expensive.
Truong Son Hy   +4 more
openaire   +2 more sources

Local molecular properties and their use in predicting reactivity

Journal of Molecular Modeling, 2003
Expressions for the local electron affinity, electronegativity and hardness are derived in analogy to the local ionization energy introduced by Sjoberg, Murray and Politzer. The local polarizability is also defined based on an additive atomic orbital polarizability model that uses Rivail's variational technique.
Bernd, Ehresmann   +3 more
openaire   +2 more sources

Attention Based Approach for Molecular Property Prediction

2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023
Tuan Tran, Chinwe Ekenna
openaire   +1 more source

Chemistry Inspired Molecular Representation for Property Prediction

Proceedings of the 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), 2022
Guna Sekhar Gedela   +2 more
openaire   +1 more source

Deep learning methods for molecular representation and property prediction

Drug Discovery Today, 2022
Mingjian Jiang, Shugang Zhang
exaly  

Towards Accurate and Certain Molecular Properties Prediction

2022 13th International Conference on Information and Communication Technology Convergence (ICTC), 2022
KyungPyo Ham, JeongNoh Yoon, Lee Sael
openaire   +2 more sources

Few-shot learning with transformers via graph embeddings for molecular property prediction

Expert Systems With Applications, 2023
Luis H M Torres   +2 more
exaly  

Molecular structure transformers for property prediction

2023
GADHIYA TUSHARKUMAR   +5 more
openaire   +2 more sources

MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction

Briefings in Bioinformatics, 2021
Tingjun Hou   +2 more
exaly  

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