Search Results - Meta-graph algorithm

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

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

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

“…Background An increasing number of biological and clinical evidences have indicated that the microorganisms significantly get involved in the pathological…”
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AMGDTI: drug–target interaction prediction based on adaptive meta-graph learning in heterogeneous network by Su, Yansen, Hu, Zhiyang, Wang, Fei, Bin, Yannan, Zheng, Chunhou, Li, Haitao, Chen, Haowen, Zeng, Xiangxiang

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

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

“… Most algorithms on HIN leverage meta-graphs or meta-paths (special cases of meta-graphs) to capture various semantics…”
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Meta graph network recommendation based on multi-behavior encoding by Xiaoyang Liu, Wei Xiao, Chao Liu, Wei Wang, Chaorong Li

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

“… In this paper, we propose a novel framework for STG learning called Dynamic Meta-Graph Convolutional Recurrent Network (DMetaGCRN…”
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A Meta-graph Approach to Analyze Subgraph-centric Distributed Programming Models by Dindokar, Ravikant, Choudhury, Neel, Simmhan, Yogesh

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

“… Using six machine learning methods, four algorithms (Random Forest, LightGBM, XGBoost, Lasso…”
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MGACL: Prediction Drug–Protein Interaction Based on Meta-Graph Association-Aware Contrastive Learning by Zhang, Pinglu, Lin, Peng, Li, Dehai, Wang, Wanchun, Qi, Xin, Li, Jing, Xiong, Jianshe

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

“… To address this issue, this paper proposes a framework that combines graph ODE and meta-graph (MG) search…”
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EMcnv: enhancing CNV detection performance through ensemble strategies with heterogeneous meta-graph neural networks by Wang, Xuwen, Chang, Zhili, Liu, Yuqian, Wang, Shenjie, Zhu, Xiaoyan, Shao, Yang, Wang, Jiayin

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

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

“… We explore the impact of various graph partitioning techniques on the meta-graph, and the impact of the meta-graph on graph algorithms…”
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WMGCN: Weighted Meta-Graph Based Graph Convolutional Networks for Representation Learning in Heterogeneous Networks by Zhang, Jinli, Jiang, Zongli, Chen, Zheng, Hu, Xiaohua

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

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

“… To solve this problem, a heterogeneous graph neural network algorithm based on meta-path convolution was proposed…”
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A Noval Weighted Meta Graph Method for Classification in Heterogeneous Information Networks by Zhang, Jinli, Li, Tong, Jiang, Zongli, Hu, Xiaohua, Jazayeri, Ali

“… In this paper, a novel framework is proposed for the weighted Meta graph-based Classification of Heterogeneous Information Networks (MCHIN…”
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AMHP-SDC: An Adaptive Semantic Meta-Graph and Hypergraph Learning Framework for Predicting Synergistic Drug Combinations by Chen, Junjie, Chen, Mengjie, Miao, Jian, Qu, Cunquan

“… To address these challenges, we propose a novel framework, AMHP-SDC, which combines adaptive semantic meta-graph learning, hypergraph learning, and drug molecular graph perception for SDCs prediction…”
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