Integrating explainability into graph neural network models for the prediction of X-ray absorption spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - ACS Publications
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …
被引用次数：8 相关文章

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - publications.hereon.de
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …
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[HTML][HTML] Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - ncbi.nlm.nih.gov
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - refubium.fu-berlin.de
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra.

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - europepmc.org
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - pubmed.ncbi.nlm.nih.gov
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - research.rug.nl
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating explainability into graph neural network models for the prediction of X-ray absorption spectra

A Kotobi, K Singh, D Höche, S Bari, R Meißner… - Journal of the American …, 2023 - tore.tuhh.de
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - repo.uni-hannover.de
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra.

A Kotobi, K Singh, D Höche, S Bari… - Journal of the …, 2023 - europepmc.org
The use of sophisticated machine learning (ML) models, such as graph neural networks
(GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly …