Results 111 to 120 of about 748,129 (177)

Encoder embedding for general graph and node classification

Applied Network Science
AbstractGraph encoder embedding, a recent technique for graph data, offers speed and scalability in producing vertex-level representations from binary graphs. In this paper, we extend the applicability of this method to a general graph model, which includes weighted graphs, distance matrices, and kernel matrices.
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Multi-grained contrastive-learning driven MLPs for node classification. [PDF]

Sci Rep
Bao Q, Huang X, Zhuang W, Pan P.
europepmc   +1 more source

A graph transformer with optimized attention scores for node classification. [PDF]

Sci Rep
Zhang Y, Li X, Xu Y, Xu X, Wang Z.
europepmc   +1 more source

Dynamic graph structure evolution for node classification with missing attributes. [PDF]

Sci Rep
Song X, Zhou B, Wang Y, Liu W.
europepmc   +1 more source

Evaluation of different lymph node classification systems as independent prognosticators in gastric signet ring cell carcinoma. [PDF]

World J Surg Oncol
Wang LF, Sun ML, Wang MQ, Wang G, Huang XJ, Chen YL, Chen YR.   +6 more
europepmc   +1 more source

Node Classification Method Based on Hierarchical Hypergraph Neural Network. [PDF]

Sensors (Basel)
Xu F, Xiong W, Fan Z, Sun L.
europepmc   +1 more source

Unifying topological structure and self-attention mechanism for node classification in directed networks. [PDF]

Sci Rep
Peng Y, Xia J, Liu D, Liu M, Xiao L, Shi B.   +5 more
europepmc   +1 more source

The role of infraclavicular and supraclavicular lymph nodes in breast cancer patients receiving neoadjuvant chemotherapy: implications for regional lymph node classification. [PDF]

J Natl Cancer Cent
Chen Y, Song Y, Han Z, Han H, Tang T, Chen S, Zhao R, Huang C, Shi G, Lin Y, Wang Y, Jiang L, Chen J, Xu C, Fu F, Wang C, Yang Y.   +16 more
europepmc   +1 more source

Validation and proposed modification of the 8th edition American Joint Committee on Cancer staging system for patients with esophageal neuroendocrine neoplasms: Evaluation of a revised lymph node classification. [PDF]

Oncol Lett, 2020
Wang H, Chen Y, Pi G, Zhu Y, Yang S, Mei H, Lin Z, Zhang T.   +7 more
europepmc   +1 more source

Adaptive Spectral-Heterophily for Node Classification

Node classification in graphs, particularly those exhibiting heterophily, poses significant challenges for traditional methodologies. These include various graph neural network variants and approaches that simplify graph convolutions. This paper proposes a novel approach called nCASH, which combines an innovative label propagation method that utilizes ...
openaire   +2 more sources