Výsledky vyhledávání - Graph autoencoder

scZIGVAE: A Variational Graph Attention Autoencoder Based on the Zero-Inflated Negative Binomial Distribution for Clustering Single-cell RNA-Seq Data

Autoři: Yutian Wang Ke Gao Zhaomei Li a další

Zdroj: Current Bioinformatics. 20:721-735

Signed versus isomorphic graph autoencoders for microRNA–single–nucleotide polymorphisms network reconstruction in periodontal osteo-genomic landscapes

Autoři: Sarvagya Sharma

Zdroj: Gaceta Médica de Caracas. 133:675-685

Importance weighted variational graph autoencoder

Autoři: Yuhao Tao Lin Guo Shuchang Zhao a další

Zdroj: Complex & Intelligent Systems, Vol 12, Iss 1, Pp 1-16 (2025)

Témata: Graph neural networks, Variational graph autoencoder, Variational inference, Importance weighted, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2199-4536; https://doaj.org/toc/2198-6053

Přístupová URL adresa: https://doaj.org/article/b111fb84353f458ab68cb00bba7ce0ad

Exploring the latent space distribution of a graph autoencoder trained on 3D models of modernist architecture

Autoři: Erik Bauscher Thomas Wortmann

Zdroj: International Journal of Architectural Computing. 23:742-752

A Novel Framework for Predicting Phage-Host Interactions via Host Specificity-Aware Graph Autoencoder

Autoři: Zhen Xiao Han Sun Ankang Wei a další

Zdroj: IEEE Journal of Biomedical and Health Informatics. 29:3069-3078

Témata: Bacteria, Host-Pathogen Interactions, Computational Biology, Humans, Bacteriophages, Autoencoder, Host Specificity, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40030240

Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes

Autoři: Yige Zhao Jianxiang Yu Yao Cheng a další

Zdroj: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1. :2067-2078

Témata: Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Social and Information Networks, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2311.07929

WAGE: Weight-Sharing Attribute-Missing Graph Autoencoder

Autoři: Wenxuan Tu Sihang Zhou Xinwang Liu a další

Zdroj: IEEE Transactions on Pattern Analysis and Machine Intelligence. 47:5760-5777

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40184302

GAE4HT: Detecting Hardware Trojans with Graph Autoencoder-Trained on Golden Model Data Flow Graphs

Autoři: Daehyeon Lee Junghee Lee

Zdroj: Proceedings of the 20th ACM Asia Conference on Computer and Communications Security. :1175-1187

Modelling and solving sustainable supply chain network design based on graph autoencoder clustering algorithm

Autoři: Yuhan Guo Runsheng Chen Youssef Boulaksil a další

Zdroj: International Journal of Production Research. :1-27

Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection

Autoři: Long Zeng Jianxiang Yu Jiapeng Zhu a další

Zdroj: Proceedings of the ACM on Web Conference 2025. :3772-3782

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2504.12715

A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation

Autoři: Yu, Huafei Ai, Tinghua Yang, Min a další

Přispěvatelé: Yu, Huafei Ai, Tinghua Yang, Min a další

Zdroj: International Journal of Digital Earth. 16(1):1828-1852

Témata: Natural Sciences, Earth and Related Environmental Sciences, Other Earth Sciences (including Geographical Information Science), Naturvetenskap, Geovetenskap och relaterad miljövetenskap, Annan geovetenskap (Här ingår: Geografisk informationsvetenskap), Physical Geography, Naturgeografi

Přístupová URL adresa: https://doi.org/10.1080/17538947.2023.2212920

Unsupervised Feature Selection via a Dual-Graph Autoencoder with l2,1/2-Norm for [68Ga]Ga-Pentixafor PET Imaging of Glioma

Autoři: Zhichao Song Meiling Chen Liang Xie a další

Zdroj: Applied Sciences, Vol 15, Iss 11, p 6177 (2025)

Témata: autoencoder, dual-graph regularization, norm, Technology, QH301-705.5, Physics, QC1-999, [68Ga]Ga-Pentixafor PET, Engineering (General). Civil engineering (General), Chemistry, TA1-2040, Biology (General), unsupervised feature selection, QD1-999

Přístupová URL adresa: https://doaj.org/article/ed87b0d06fcd4ee2ac12fa482729fe02

Self-supervised Graph Autoencoder with Node Feature Convolution for Community Detection

Autoři: Haoran Tan Hongkai Xie Xiaofeng Wang a další

Zdroj: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783032002174

Deciphering metabolic disease mechanisms for natural medicine discovery via graph autoencoders

Autoři: Qingquan Liao Wei Zhao Zhan Wang a další

Zdroj: Front Pharmacol
Frontiers in Pharmacology, Vol 16 (2025)

Témata: Pharmacology, graph autoencoder, metabolite-disease associations, Therapeutics. Pharmacology, RM1-950, metabolic diseases, natural medicines, drug discovery

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40337507
https://doaj.org/article/486bbb1f80b5439d819efc0e87ed0692

Enhancing Recommendation Performance via Aspect-Based Review Analysis and Dual Graph Autoencoder

Autoři: Dasom Jeong Haebin Lim Qinglong Li a další

Zdroj: Journal of Intelligence and Information Systems. 31:111-130

DGAEPPO: Graph Autoencoder-Enhanced PPO for Dependency-Aware Edge Tasks

Autoři: Bofeng Zhang Chenlei Xu Simin Wang a další

Zdroj: 2025 IEEE 6th International Conference on Pattern Recognition and Machine Learning (PRML). :134-138

scE2EGAE: enhancing single-cell RNA-Seq data analysis through an end-to-end cell-graph-learnable graph autoencoder with differentiable edge sampling

Autoři: Shuo Wang Yuanning Liu Hao Zhang a další

Zdroj: Biology Direct, Vol 20, Iss 1, Pp 1-25 (2025)

Témata: Single-cell RNA-Seq, Bioinformatics, End-to-end, Graph neural networks, Deep learning, Autoencoder, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1745-6150

Přístupová URL adresa: https://doaj.org/article/4525536cd6c9495e9b605c48d89eed07

VCGAE++: variational collective graph autoEncoder for multi-behavior recommendation

Autoři: Yingxuan Zhuang Yang Liu Weike Pan a další

Zdroj: Knowledge and Information Systems. 67:8085-8114

Locational False Data Injection Attack Detection in Smart Grid Using Recursive Variational Graph Autoencoder

Autoři: Yufeng Wang Ziyan Lu Jianhua Ma a další

Zdroj: IEEE Internet of Things Journal. 12:13697-13708

Canonical Correlation Analysis aided Dynamic Graph Autoencoder Method for Industrial Process Monitoring

Autoři: Md Mehedi Hassan Zhiwen Chen Syeda Sadia Afrin a další

Zdroj: 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). :750-755