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First is Node2Vec, a popular graph embedding algorithm that uses neural networks to learn continuous feature representations for nodes, which can then be used for downstream machine learning tasks.
GNNs is considered state of the art in machine learning, and they can have better accuracy in making predictions compared to conventional neural networks. Integrating GNNs with graph databases is ...
More information: Xiaorui Su et al, Interpretable identification of cancer genes across biological networks via ...
More information: Janghoon Ock et al, Multimodal language and graph learning of adsorption configuration in catalysis, Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00930-7 . On ...
Next-generation graph data and analytics platform now with machine learning and data science features to accelerate innovation SAN FRANCISCO, Oct. 11, 2023 /PRNewswire/ -- ArangoDB, the ...
News-Medical.Net on MSN9d
Machine learning boosts accuracy of point-of-care disease detectionWhat if people could detect cancer and other diseases with the same speed and ease of a pregnancy test or blood glucose meter ...
An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design ...
More information: Janghoon Ock et al, Multimodal language and graph learning of adsorption configuration in catalysis, Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00930-7 . On ...
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