Suchergebnisse - Meta-graph algorithm

  1. 1

    A domain generalization pedestrian re-identification algorithm based on meta-graph aware von Wu, Dongyang, Zhang, Baohua, Lu, Xiaoqi, Li, Yongxiang, Gu, Yu, Li, Jianjun, Ren, Guoyin

    ISSN: 1380-7501, 1573-7721
    Veröffentlicht: New York Springer US 01.01.2024
    Veröffentlicht in Multimedia tools and applications (01.01.2024)
    “… This paper proposes a person re-identification algorithm based on meta-graph aware (Meta-GA) under the framework of meta-learning, which includes two stages …”
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    Journal Article
  2. 2

    From spatial to spectral: Network renormalization via dynamical correlations von Kim, Cook Hyun, Kahng, B.

    ISSN: 0960-0779
    Veröffentlicht: Elsevier Ltd 01.12.2025
    Veröffentlicht in Chaos, solitons and fractals (01.12.2025)
    “… Building on this foundation, we develop a meta-graph reconstruction algorithm that systematically maps spectral information back into explicit topology while preserving dynamical correlations …”
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    Journal Article
  3. 3

    WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network von Long, Yahui, Luo, Jiawei

    ISSN: 1471-2105, 1471-2105
    Veröffentlicht: London BioMed Central 01.11.2019
    Veröffentlicht in BMC bioinformatics (01.11.2019)
    “… Background An increasing number of biological and clinical evidences have indicated that the microorganisms significantly get involved in the pathological …”
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    Journal Article
  4. 4

    AMGDTI: drug–target interaction prediction based on adaptive meta-graph learning in heterogeneous network von Su, Yansen, Hu, Zhiyang, Wang, Fei, Bin, Yannan, Zheng, Chunhou, Li, Haitao, Chen, Haowen, Zeng, Xiangxiang

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Veröffentlicht: England Oxford Publishing Limited (England) 01.01.2024
    Veröffentlicht in Briefings in bioinformatics (01.01.2024)
    “… Although network representation learning algorithms have achieved success in predicting DTI, several manually designed meta-graphs limit the capability of extracting complex semantic information …”
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    Journal Article
  5. 5

    DTiGNN: Learning drug-target embedding from a heterogeneous biological network based on a two-level attention-based graph neural network von Muniyappan, Saranya, Rayan, Arockia Xavier Annie, Varrieth, Geetha Thekkumpurath

    ISSN: 1551-0018, 1551-0018
    Veröffentlicht: United States AIMS Press 01.01.2023
    Veröffentlicht in Mathematical biosciences and engineering : MBE (01.01.2023)
    “… Motivation: In vitro experiment-based drug-target interaction (DTI) exploration demands more human, financial and data resources. In silico approaches have …”
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    Journal Article
  6. 6

    Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights von Yang, Carl, Feng, Yichen, Li, Pan, Shi, Yu, Han, Jiawei

    ISSN: 2374-8486
    Veröffentlicht: IEEE 01.11.2018
    “… Most algorithms on HIN leverage meta-graphs or meta-paths (special cases of meta-graphs) to capture various semantics …”
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    Tagungsbericht
  7. 7

    Meta graph network recommendation based on multi-behavior encoding von Xiaoyang Liu, Wei Xiao, Chao Liu, Wei Wang, Chaorong Li

    ISSN: 1319-1578
    Veröffentlicht: Springer 01.06.2024
    “… We propose a meta-graph network recommendation system via multi-behavior encoding (MBGR). Firstly, the graph convolutional neural network is used to extract features …”
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    Journal Article
  8. 8

    Dynamic meta-graph convolutional recurrent network for heterogeneous spatiotemporal graph forecasting von Guo, Xianwei, Yu, Zhiyong, Huang, Fangwan, Chen, Xing, Yang, Dingqi, Wang, Jiangtao

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Veröffentlicht: United States Elsevier Ltd 01.01.2025
    Veröffentlicht in Neural networks (01.01.2025)
    “… In this paper, we propose a novel framework for STG learning called Dynamic Meta-Graph Convolutional Recurrent Network (DMetaGCRN …”
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    Journal Article
  9. 9

    A Meta-graph Approach to Analyze Subgraph-centric Distributed Programming Models von Dindokar, Ravikant, Choudhury, Neel, Simmhan, Yogesh

    ISSN: 2331-8422
    Veröffentlicht: Ithaca Cornell University Library, arXiv.org 31.10.2016
    Veröffentlicht in arXiv.org (31.10.2016)
    “… However, there is limited literature on foundational aspects of the behavior of these component-centric abstractions for different graphs, graph partitioning, and graph algorithms …”
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    Paper
  10. 10

    Immune status assessment based on plasma proteomics with meta graph convolutional networks von Zhang, Min, Xu, Nan, Cheng, Qi, Ye, Jing, Wu, Shiwei, Liu, Haoliang, Zhao, Chengkui, Yu, Lei, Feng, Weixing

    ISSN: 1471-2164, 1471-2164
    Veröffentlicht: London BioMed Central 10.04.2025
    Veröffentlicht in BMC genomics (10.04.2025)
    “… Using six machine learning methods, four algorithms (Random Forest, LightGBM, XGBoost, Lasso …”
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    Journal Article
  11. 11

    MGACL: Prediction Drug–Protein Interaction Based on Meta-Graph Association-Aware Contrastive Learning von Zhang, Pinglu, Lin, Peng, Li, Dehai, Wang, Wanchun, Qi, Xin, Li, Jing, Xiong, Jianshe

    ISSN: 2218-273X, 2218-273X
    Veröffentlicht: Switzerland MDPI AG 01.10.2024
    Veröffentlicht in Biomolecules (Basel, Switzerland) (01.10.2024)
    “… named Meta Graph Association-Aware Contrastive Learning (MGACL), which can transfer personalized heterogeneous auxiliary information from different nodes and reduce data bias …”
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    Journal Article
  12. 12

    Spatio-Temporal Meta-Graph Learning for Recommendation on Heterogeneous Graphs von Yang, Xiaofei, Yang, Wenjing, Wang, Xiaoshuang, Gao, Mei, Zhang, Lu

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2025
    Veröffentlicht in IEEE access (2025)
    “… To address this issue, this paper proposes a framework that combines graph ODE and meta-graph (MG) search …”
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    Journal Article
  13. 13

    EMcnv: enhancing CNV detection performance through ensemble strategies with heterogeneous meta-graph neural networks von Wang, Xuwen, Chang, Zhili, Liu, Yuqian, Wang, Shenjie, Zhu, Xiaoyan, Shao, Yang, Wang, Jiayin

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Veröffentlicht: England Oxford University Press 04.03.2025
    Veröffentlicht in Briefings in bioinformatics (04.03.2025)
    “… Abstract Copy number variation (CNV) is a crucial biomarker for many complex traits and diseases. Although numerous CNV detection tools are available, no …”
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    Journal Article
  14. 14

    Meta-graph Embedding in Heterogeneous Information Network for Top-N Recommendation von Bai, Lin, Cai, Chengye, Liu, Jie, Ye, Dan

    ISSN: 2161-4407
    Veröffentlicht: IEEE 18.07.2021
    “… or other analogous recommendation algorithms. In this paper, we propose a novel meta-graph embedding based deep learning recommendation model, MGRec …”
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    Tagungsbericht
  15. 15

    A meta-graph approach to analyze subgraph-centric distributed programming models von Dindokar, Ravikant, Choudhury, Neel, Simmhan, Yogesh

    Veröffentlicht: IEEE 01.12.2016
    “… We explore the impact of various graph partitioning techniques on the meta-graph, and the impact of the meta-graph on graph algorithms …”
    Volltext
    Tagungsbericht
  16. 16

    Meta-path convolution based heterogeneous graph neural network algorithm von Qin, Zhilong, Deng, Kun, Liu, Xingyan

    ISSN: 1000-0801
    Veröffentlicht: Bejing China International Book Trading 01.03.2024
    Veröffentlicht in Dianxin Kexue (01.03.2024)
    “… To solve this problem, a heterogeneous graph neural network algorithm based on meta-path convolution was proposed …”
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    Journal Article
  17. 17

    WMGCN: Weighted Meta-Graph Based Graph Convolutional Networks for Representation Learning in Heterogeneous Networks von Zhang, Jinli, Jiang, Zongli, Chen, Zheng, Hu, Xiaohua

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2020
    Veröffentlicht in IEEE access (2020)
    “… Network embedding has been an effective tool to analyze heterogeneous networks (HNs) by representing nodes in a low-dimensional space. Although many recent …”
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    Journal Article
  18. 18

    Stochastic dynamic power dispatch with high generalization and few-shot adaption via contextual meta graph reinforcement learning von Huang, Zhanhong, Yu, Tao, Pan, Zhenning, Deng, Bairong, Zhang, Xuehan, Wu, Yufeng, Ding, Qiaoyi

    ISSN: 0142-0615
    Veröffentlicht: Elsevier Ltd 01.11.2024
    “… To fill these gaps, a novel contextual meta graph reinforcement learning (Meta-GRL) method a more general contextual Markov decision process (CMDP …”
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    Journal Article
  19. 19

    Meta-path convolution based heterogeneous graph neural network algorithm von QIN Zhilong, DENG Kun, LIU Xingyan

    ISSN: 1000-0801
    Veröffentlicht: Beijing Xintong Media Co., Ltd 01.03.2024
    Veröffentlicht in Dianxin Kexue (01.03.2024)
    “… To solve this problem, a heterogeneous graph neural network algorithm based on meta-path convolution was proposed …”
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    Journal Article
  20. 20

    A Noval Weighted Meta Graph Method for Classification in Heterogeneous Information Networks von Zhang, Jinli, Li, Tong, Jiang, Zongli, Hu, Xiaohua, Jazayeri, Ali

    ISSN: 2076-3417, 2076-3417
    Veröffentlicht: MDPI AG 01.03.2020
    Veröffentlicht in Applied sciences (01.03.2020)
    “… In this paper, a novel framework is proposed for the weighted Meta graph-based Classification of Heterogeneous Information Networks (MCHIN …”
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    Journal Article