Results 231 to 240 of about 409,466 (266)

Retraction Note: Knowledge graph driven medicine recommendation system using graph neural networks on longitudinal medical records. [PDF]

Sci Rep
Mishra R, Shridevi S.
europepmc   +1 more source

Efficient Learning of Molecular Properties Using Graph Neural Networks Enhanced with Chemistry Knowledge. [PDF]

ACS Omega
Lutchyn T, Mardal M, Ricaud B.
europepmc   +1 more source

Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults. [PDF]

Proc ACM Int Conf Inf Knowl Manag
Jeon DH, Zhu L, Li H, Li P, Feng J, Duan T, Song HH, Tao C, Niu S.   +8 more
europepmc   +1 more source

Integrative Spatial Modelling of Cellular Plasticity using Graph Neural Networks and Geostatistics

Withnell E, Celik C, Secrier M.
europepmc   +1 more source

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Graph neural networks

Nature Reviews Methods Primers
Gabriele Corso, Hannes Stark, Stefanie Jegelka, Tommi Jaakkola, Regina Barzilay   +4 more
exaly   +6 more sources

Graph Neural Networks

2021
Graphs are universal representations of pairwise relations with many real-world applications. In the healthcare domain, graphs are widely observed as relations of biomedical entities, including the graph structures of molecules, drug-drug interaction networks, protein-protein interaction networks, and gene expression networks and biomedical knowledge ...
Cao Xiao, Jimeng Sun
  +6 more sources

Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks

2023
Neural networks that can process the parameters of other neural networks find applications in diverse domains, including processing implicit neural representations, domain adaptation of pretrained networks, generating neural network weights, and predicting generalization errors.
Zhang, D.W., Kofinas, M., Zhang, Y., Chen, Y., Burghouts, G.J., Snoek, C.G.M.   +5 more
openaire   +1 more source