Suchergebnisse - Heterogeneous graph autoencoder

NodeHGAE: Node-oriented heterogeneous graph autoencoder von Zhu, Xiangkai, Li, Chao, Yan, Yeyu, Zhao, Zhongying, Duan, Hua, Zeng, Qingtian

“… Heterogeneous graph autoencoder (HGAE), as an unsupervised learning approach, aims to encode nodes and edges of heterogeneous graphs into low-dimensional vector representations, and simultaneously reconstruct the original graph structure …”
Volltext

Conditional Enhanced Variational Autoencoder-Heterogeneous Graph Attention Neural Network: A Novel Fault Diagnosis Method for Electric Rudders Based on Heterogeneous Information von Cao, Ximing, Yang, Ruifeng, Guo, Chenxia, Qin, Hao

“… In machine fault diagnosis, despite the wealth of information multi-sensor data provide for constructing high-quality graphs, existing graph data-driven diagnostic methods face challenges posed …”
Volltext

Hgae: Heterogeneous Graph Autoencoder-Based Service Bundle Recommendations for Efficient Mashup Development von Sun, Kaipu, Wang, Xuanye, Xi, Meng, Wu, Yangyang, Pan, Xiaohua, Zhang, Jinshan, Li, Ying, Ma, Kun, Yin, Jianwei

“… In this work, we propose an innovative message-passing model, a Heterogeneous Graph AutoEncoderbased service bundle recommendation model (HGAE …”
Volltext

Deceptive reviewer group detection using self-adversarial variational autoencoder: a heterogeneous graph-based approach von Maurya, Sushil Kumar, Singh, Dinesh

“… by completing the user-review-product graph. To accomplish this, we propose an integrated approach comprising three key components …”
Volltext

V-GMR: a variational autoencoder-based heterogeneous graph multi-behavior recommendation model von Yang, Haoqin, Rang, Ran, Xing, Linlin, Zhang, Longbo, Cai, Hongzhen, Guo, Maozu, Sun, Jiaqi

“… In this paper, we propose a variational autoencoder (VAE) and graph-based heterogeneous multibehavior recommendation model (V-GMR …”
Volltext

VHGAE: Drug-Target Interaction Prediction Model Based on Heterogeneous Graph Variational Autoencoder von Zhang, Chen, Sun, Jiaqi, Xing, Linlin, Zhang, Longbo, Cai, Hongzhen, Che, Kai

“… the prediction performance of DTI. Therefore, we propose a method, called VHGAE, based on a heterogeneous graph variational autoencoder to predict drug-target interactions …”
Volltext

MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data von Zhao, Jinhui, He, Jiarui, Guan, Pengwei, Bao, Han, Zhao, Xinjie, Zhao, Chunxia, Qin, Wangshu, Lu, Xin, Xu, Guowang

“… To address these critical limitations, we introduce MODAPro, a biologically informed deep learning framework that synergistically integrates variational graph autoencoders (VAE …”
Weitere Angaben

GIAE-DTI: Predicting Drug-Target Interactions Based on Heterogeneous Network and GIN-Based Graph Autoencoder von Wang, Mengdi, Lei, Xiujuan, Liu, Lian, Chen, Jianrui, Wu, Fang-Xiang

“… -modal similarity of drugs and targets and constructs a heterogeneous network for DTI prediction …”
Volltext

SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival von Pan, Liangrui, Peng, Yijun, Li, Yan, Wang, Xiang, Liu, Wenjuan, Xu, Liwen, Liang, Qingchun, Peng, Shaoliang

“… This paper introduces SELECTOR, a heterogeneous graph-aware network based on convolutional mask encoders for robust multimodal prediction of cancer patient survival …”
Volltext

GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network von Liu, Zhixian, Chen, Qingfeng, Lan, Wei, Pan, Haiming, Hao, Xinkun, Pan, Shirui

“… In this article, a graph autoencoder approach for DTI prediction (GADTI) was proposed to discover potential interactions between drugs and targets using a heterogeneous network, which integrates diverse drug-related and target-related datasets …”
Volltext

Drug repositioning based on heterogeneous networks and variational graph autoencoders von Lei, Song, Lei, Xiujuan, Liu, Lian

“…  years has facilitated drug development. In this study we propose a drug repositioning method, VGAEDR, based on a heterogeneous network of multiple drug attributes and a variational graph autoencoder …”
Volltext

Predicting potential microbe-disease associations based on heterogeneous graph attention network and deep sparse autoencoder von Wang, Bo, Zhao, Wenlong, Du, Xiaoxin, Zhang, Jianfei, Zhang, Chunyu, Wang, Liping, He, Yang

“… We propose a computational framework called graph attention convolutional deep sparse autoencoder microbe-disease association (GCDSAEMDA …”
Volltext

AEGCN: An Autoencoder-Constrained Graph Convolutional Network von Ma, Mingyuan, Na, Sen, Wang, Hongyu

“… We consider applying our model on both homogeneous graphs and heterogeneous graphs. For homogeneous graphs, the autoencoder approximates to the adjacency matrix …”
Volltext

Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images von Jia, Meng, Lou, Xiangyu, Zhao, Zhiqiang, Lu, Xiaofeng, Shi, Zhenghao

“… To address this issue, we propose the Multi-Head Graph Attention Mechanism (MHGAN), designed to achieve accurate detection of surface changes in heterogeneous remote sensing images …”
Volltext

Heterogeneous Graph Masked Autoencoders von Tian, Yijun, Dong, Kaiwen, Zhang, Chunhui, Zhang, Chuxu, Chawla, Nitesh V

“… ? In light of this, we study the problem of generative SSL on heterogeneous graphs and propose HGMAE, a novel heterogeneous graph masked autoencoder model to address these challenges …”
Volltext

Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes von Zhao, Yige, Yu, Jianxiang, Cheng, Yao, Yu, Chengcheng, Liu, Yiding, Li, Xiang, Wang, Shuaiqiang

“… Heterogeneous Information Networks (HINs), which consist of various types of nodes and edges, have recently demonstrated excellent performance in graph mining …”
Volltext

Exploring Microbe-Drug Association Prediction via Multi-Attribute Dual-Decoder Graph Autoencoder von Liu, Wei, Deng, Xiangcheng, Sun, Xingen, Lu, Xu, Chen, Xing

“… In this work, we propose a method called exploring microbe-drug association prediction via multi-attribute dual-decoder graph autoencoder (MDGAEMDA …”
Volltext

Dataset Recommendation via Variational Graph Autoencoder von Altaf, Basmah, Akujuobi, Uchenna, Yu, Lu, Zhang, Xiangliang

“… This paper targets on designing a query-based dataset recommendation system, which accepts a query denoting a user's research interest as a set of research …”
Volltext

GSAMDA: a computational model for predicting potential microbe–drug associations based on graph attention network and sparse autoencoder von Tan, Yaqin, Zou, Juan, Kuang, Linai, Wang, Xiangyi, Zeng, Bin, Zhang, Zhen, Wang, Lei

“… Results In this work, we proposed a novel computational model named GSAMDA based on the graph attention network and sparse autoencoder to infer latent microbe–drug associations …”
Volltext

MSGCA: Drug-Disease Associations Prediction Based on Multi-Similarities Graph Convolutional Autoencoder von Wang, Ying, Gao, Ying-Lian, Wang, Juan, Li, Feng, Liu, Jin-Xing

“… Hence, a prediction method based on multi-similarities graph convolutional autoencoder (MSGCA …”
Volltext