Cargando…

Graph Autoencoder with Preserving Node Attribute Similarity

The graph autoencoder (GAE) is a powerful graph representation learning tool in an unsupervised learning manner for graph data. However, most existing GAE-based methods typically focus on preserving the graph topological structure by reconstructing the adjacency matrix while ignoring the preservatio...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lin, Mugang, Wen, Kunhui, Zhu, Xuanying, Zhao, Huihuang, Sun, Xianfang
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138145/ https://www.ncbi.nlm.nih.gov/pubmed/37190356 http://dx.doi.org/10.3390/e25040567

Ejemplares similares

Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes
por: Khan, Wasif, et al.
Publicado: (2023)

GRACE: Graph autoencoder based single-cell clustering through ensemble similarity learning
por: Ha, Jun Seo, et al.
Publicado: (2023)

Robust Attribute and Structure Preserving Graph Embedding
por: Hettige, Bhagya, et al.
Publicado: (2020)

Scalably Using Node Attributes and Graph Structure for Node Classification †
por: Merchant, Arpit, et al.
Publicado: (2022)

Representation Learning: Recommendation With Knowledge Graph via Triple-Autoencoder
por: Geng, Yishuai, et al.
Publicado: (2022)

A topology-preserving dimensionality reduction method for single-cell RNA-seq data using graph autoencoder
por: Luo, Zixiang, et al.
Publicado: (2021)

Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation
por: Kwon, Youngchun, et al.
Publicado: (2019)

Auxiliary Graph for Attribute Graph Clustering
por: Li, Wang, et al.
Publicado: (2022)

IRC-Safe Graph Autoencoder for Unsupervised Anomaly Detection
por: Atkinson, Oliver, et al.
Publicado: (2022)

Coupled Node Similarity Learning for Community Detection in Attributed Networks
por: Meng, Fanrong, et al.
Publicado: (2018)

Synthetic electronic health records generated with variational graph autoencoders
por: Nikolentzos, Giannis, et al.
Publicado: (2023)

Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization
por: Choong, Jun Jin, et al.
Publicado: (2020)

Generating tertiary protein structures via interpretable graph variational autoencoders
por: Guo, Xiaojie, et al.
Publicado: (2021)

Drug repositioning based on heterogeneous networks and variational graph autoencoders
por: Lei, Song, et al.
Publicado: (2022)

Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
por: Tsan, Steven, et al.
Publicado: (2021)

SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder
por: Wang, Shudong, et al.
Publicado: (2022)

Single-cell RNA-seq data analysis using graph autoencoders and graph attention networks
por: Feng, Xiang, et al.
Publicado: (2022)

GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network
por: Liu, Zhixian, et al.
Publicado: (2021)

Malware detection framework based on graph variational autoencoder extracted embeddings from API-call graphs
por: Gunduz, Hakan
Publicado: (2022)

GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder
por: Li, Lei, et al.
Publicado: (2021)

Feature Reduction for Molecular Similarity Searching Based on Autoencoder Deep Learning
por: Nasser, Maged, et al.
Publicado: (2022)

Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks
por: Rao, Jiahua, et al.
Publicado: (2021)

Formal Verification of Invariants for Attributed Graph Transformation Systems Based on Nested Attributed Graph Conditions
por: Schneider, Sven, et al.
Publicado: (2020)

Relative Entropy of Distance Distribution Based Similarity Measure of Nodes in Weighted Graph Data
por: Liu, Shihu, et al.
Publicado: (2022)

VGAEDTI: drug-target interaction prediction based on variational inference and graph autoencoder
por: Zhang, Yuanyuan, et al.
Publicado: (2023)

Graph Variational Autoencoder for Detector Reconstruction and Fast Simulation in High-Energy Physics
por: Hariri, Ali
Publicado: (2021)

Overlapping Community Detection Based on Attribute Augmented Graph
por: Lin, Hanyang, et al.
Publicado: (2021)

Reflecting on Graphs: Attributes of Graph Choice and Construction Practices in Biology
por: Angra, Aakanksha, et al.
Publicado: (2017)

SQEIR: An epidemic virus spread analysis and prediction model
por: Wu, Yichun, et al.
Publicado: (2022)

Graph-based prediction of Protein-protein interactions with attributed signed graph embedding
por: Yang, Fang, et al.
Publicado: (2020)

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks
por: Yang, Yongjian, et al.
Publicado: (2023)

Unfolding Symbolic Attributed Graph Grammars
por: Ghaffari Saadat, Maryam, et al.
Publicado: (2020)

Drug-target interaction prediction based on spatial consistency constraint and graph convolutional autoencoder
por: Chen, Peng, et al.
Publicado: (2023)

Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders
por: Liao, Qingquan, et al.
Publicado: (2023)

Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model
por: Wang, Jiacheng, et al.
Publicado: (2023)

Magic and antimagic graphs: attributes, observations and challenges in graph labelings
por: Bača, Martin, et al.
Publicado: (2019)

GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization
por: Chen, Hung-I Harry, et al.
Publicado: (2018)

Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder
por: Peng, Jiajie, et al.
Publicado: (2019)

MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders
por: Zhang, Peng, et al.
Publicado: (2023)

A Relationship Prediction Method for Magnaporthe oryzae–Rice Multi-Omics Data Based on WGCNA and Graph Autoencoder
por: Zhao, Enshuang, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_62a462i0vhhlfn57kths3uglaj