Výsledky vyhledávání - "Variational graph autoencoder"

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

HPOseq: a deep ensemble model for predicting the protein-phenotype relationships based on protein sequences

Autoři: Kai Zhao Zhuocheng Ji Linlin Zhang a další

Zdroj: BMC Bioinformatics, Vol 26, Iss 1, Pp 1-15 (2025)

Témata: Ensemble model, Variational graph autoencoder, Deep learning, Amino acid sequence, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2105

Přístupová URL adresa: https://doaj.org/article/c576aff5241d4fa0b88361542a81d0ad

Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines

Autoři: Zhina Wang Yangyuan Chen Hongming Ma a další

Zdroj: Front Pharmacol
Frontiers in Pharmacology, Vol 15 (2025)

Témata: Pharmacology, lung cancer, redevelopment of traditional medicines, variational graph autoencoder (VGAE), snoRNA therapeutic targets, Therapeutics. Pharmacology, RM1-950, artificial intelligence (AI)

Přístupová URL adresa: https://doaj.org/article/c553efc486264dfca34df3bbee44c6bc

Prediction of Associations between Nanoparticle, Drug and Cancer Using Variational Graph Autoencoder

Autoři: Emrah İNAN

Zdroj: Volume: 26, Issue: 76 167-172
Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi

Témata: Bilgisayar Görüşü ve Çoklu Ortam Hesaplama (Diğer), Varyasyonel Çizge Otokodlayıcı, Nanoparçacıklar, İlaç-hastalık İlişkisi, Variational Graph Autoencoder, Nanoparticles, Drug–disease Association, Computer Vision and Multimedia Computation (Other), 3. Good health

Popis souboru: application/pdf

Přístupová URL adresa: https://dergipark.org.tr/tr/pub/deumffmd/issue/82757/1300214

A one-step graph clustering method on heterogeneous graphs via variational graph embedding

Autoři: Chuang Ma Helong Xia

Zdroj: Electronic Research Archive, Vol 32, Iss 4, Pp 2772-2788 (2024)

Témata: T57-57.97, Applied mathematics. Quantitative methods, heterogeneous graph, graph cluster, QA1-939, 0202 electrical engineering, electronic engineering, information engineering, graph neural network, 02 engineering and technology, variational graph autoencoder, Mathematics

Přístupová URL adresa: https://doaj.org/article/8d75186f49114cfc9fc0e5201f30ccc3

Joint Spectral–Spatial Representation Learning for Unsupervised Hyperspectral Image Clustering

Autoři: Xuanhao Liu Taimao Wang Xiaofeng Wang

Zdroj: Applied Sciences, Vol 15, Iss 16, p 8935 (2025)

Témata: hyperspectral image clustering, graph attention network, variational graph autoencoder, quantum particle swarm optimization, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/15/16/8935; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/39fc07e9b34247dfbb478899b58a9ef9

Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation

Autoři: Huan Zhu Hongxia Hao Liang Yu

Zdroj: BMC Biology, Vol 22, Iss 1, Pp 1-15 (2024)

Témata: Variational graph autoencoder, Microbe-disease association, Signed message propagation, XGBoost, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1741-7007

Přístupová URL adresa: https://doaj.org/article/dac9fc4571f045d086486c10341093e2

Analysis of China’s High-Speed Railway Network Using Complex Network Theory and Graph Convolutional Networks

Autoři: Zhenguo Xu Jun Li Irene Moulitsas a další

Zdroj: Big Data and Cognitive Computing ; Volume 9 ; Issue 4 ; Pages: 101

Témata: key node identification, community detection, link prediction, small-world network, graph attention networks, variational graph autoencoder, network efficiency and robustness

Popis souboru: application/pdf

Relation: https://dx.doi.org/10.3390/bdcc9040101

Dostupnost: https://doi.org/10.3390/bdcc9040101

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

Autoři: Huan Zhu Hongxia Hao Liang Yu

Zdroj: BMC Biology, Vol 21, Iss 1, Pp 1-15 (2023)

Témata: Variational graph autoencoder, Wasserstein distance, Microbe-disease association, XGBoost, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1741-7007

Přístupová URL adresa: https://doaj.org/article/9df9f57d7db64eb1807009ed91888afe

Semantic-Enhanced Variational Graph Autoencoder for Movie Recommendation: An Innovative Approach Integrating Plot Summary Information and Contrastive Learning Strategy

Autoři: Wang, Mingye Hu, Xiaohui Xie, Pan a další

Zdroj: Information Technology and Control ; Vol. 53 No. 2 (2024); 570-583 ; 2335-884X ; 1392-124X

Témata: Variational graph autoencoder, recommender system, graph neural network, semantic vectors, deep learning, contrastive learning

Popis souboru: application/pdf

Relation: https://itc.ktu.lt/index.php/ITC/article/view/35689/16456; https://itc.ktu.lt/index.php/ITC/article/view/35689

Dostupnost: https://itc.ktu.lt/index.php/ITC/article/view/35689

Link Activation Using Variational Graph Autoencoders

Autoři: Saeed Jamshidiha Vahid Pourahmadi Abbas Mohammadi a další

Zdroj: IEEE Communications Letters. 25:2358-2361

Témata: Bayesian deep learning, wireless networks, Graph embedding, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, variational graph autoencoder

Popis souboru: application/pdf

Přístupová URL adresa: http://jultika.oulu.fi/files/nbnfi-fe2021101450946.pdf
http://urn.fi/urn:nbn:fi-fe2021101450946

scVGATAE: A Variational Graph Attentional Autoencoder Model for Clustering Single-Cell RNA-seq Data

Autoři: Lijun Liu Xiaoyang Wu Jun Yu a další

Zdroj: Biology, Vol 13, Iss 9, p 713 (2024)

Témata: scRNA-seq, unsupervised clustering, variational graph autoencoder, graph attention networks, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2079-7737/13/9/713; https://doaj.org/toc/2079-7737

Přístupová URL adresa: https://doaj.org/article/6e18ca828f904b919c419f513f2be47b

Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation

Autoři: Liang, Guojun Abiri, Najmeh Hashemi, Atiye Sadat a další

Přispěvatelé: Liang, Guojun Abiri, Najmeh Hashemi, Atiye Sadat a další

Témata: Probability Theory and Statistics, Diffusion model, imputation, multivariate time series, variational graph autoencoder

Relation: http://dx.doi.org/10.1109/ICASSP49660.2025.10888912; scopus:105003891405

Dostupnost: https://lup.lub.lu.se/record/ba804bc3-0bb9-4239-b6d2-54f9ef1e9c7f
https://doi.org/10.1109/ICASSP49660.2025.10888912

De novo reconstruction of cell interaction landscapes from single-cell spatial transcriptome data with DeepLinc

Autoři: Runze Li Xuerui Yang

Zdroj: Genome Biology, Vol 23, Iss 1, Pp 1-24 (2022)

Témata: Single-cell spatial transcriptome, Cell interaction, Variational graph autoencoder, VGAE, Deep learning, Biology (General), QH301-705.5, Genetics, QH426-470

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1474-760X

Přístupová URL adresa: https://doaj.org/article/2e8dd2b4f9d942369b5340796ece6ba8

Graph-Deep-Learning-Based Inference of Fine-Grained Air Quality From Mobile IoT Sensors

Autoři: Tien Huu Do Evaggelia Tsiligianni Xuening Qin a další

Přispěvatelé: Tien Huu Do Evaggelia Tsiligianni Xuening Qin a další

Zdroj: IEEE Internet of Things Journal. 7:8943-8955

Témata: IoT, variational graph autoencoder (VGAE), Smart Cities, 13. Climate action, nternet of Things (IoT), 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Deep learning, 02 engineering and technology, 7. Clean energy

Přístupová URL adresa: https://dblp.uni-trier.de/db/journals/iotj/iotj7.html#DoTQHMPD20
https://ieeexplore.ieee.org/abstract/document/9106368
https://biblio.ugent.be/publication/8676438
https://researchportal.vub.be/nl/publications/graph-deep-learning-based-inference-of-fine-grained-air-quality-f
https://biblio.vub.ac.be/vubir/graphdeeplearningbased-inference-of-finegrained-air-quality-from-mobile-iot-sensors(c1df178b-dd01-4bce-ab81-ec9243b2b964).html

Adversarial Attention-Based Variational Graph Autoencoder

Autoři: Ziqiang Weng Weiyu Zhang Wei Dou

Zdroj: IEEE Access, Vol 8, Pp 152637-152645 (2020)

Témata: 0202 electrical engineering, electronic engineering, information engineering, adversarial mechanism, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Attention layers, variational graph autoencoder, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09171337.pdf
https://doaj.org/article/36c14220733f4a9a88d0654312455cd5
https://ieeexplore.ieee.org/document/9171337
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002232113431020
https://dblp.uni-trier.de/db/journals/access/access8.html#WengZD20

scGMM-VGAE: a Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data

Autoři: Eric Lin Boyuan Liu Leann Lac a další

Zdroj: Machine Learning: Science and Technology, Vol 4, Iss 3, p 035013 (2023)

Témata: Gaussian mixture model, variational graph autoencoder, single cell RNA-seq, scGMM-VGAE, cell type, model integration, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Relation: https://doi.org/10.1088/2632-2153/acd7c3; https://doaj.org/toc/2632-2153; https://doaj.org/article/2ad3fa2850704c3a942a46b003492d03

Dostupnost: https://doi.org/10.1088/2632-2153/acd7c3
https://doaj.org/article/2ad3fa2850704c3a942a46b003492d03

scVGAMF: a novel imputation method for scRNA-seq data by integrating linear and non-linear features.

Autoři: Zhou, Zhiyuan Zhang, Wei Zheng, Xiaoying a další

Zdroj: Brief Bioinform ; ISSN:1477-4054 ; Volume:26 ; Issue:5

Témata: imputation, non-negative matrix factorization, scRNA-seq data, variational graph autoencoder

Relation: https://doi.org/10.1093/bib/bbaf562; https://pubmed.ncbi.nlm.nih.gov/41139927; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12554638/

Dostupnost: https://doi.org/10.1093/bib/bbaf562
https://pubmed.ncbi.nlm.nih.gov/41139927
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12554638/

Link activation using variational graph autoencoders

Autoři: Jamshidiha, S. (Saeed) Pourahmadi, V. (Vahid) Mohammadi, A. (Abbas) a další

Témata: Bayesian deep learning, Graph embedding, variational graph autoencoder, wireless networks

Popis souboru: application/pdf

Dostupnost: http://urn.fi/urn:nbn:fi-fe2021101450946

Interpretable Variational Graph Autoencoder with Noninformative Prior

Autoři: Lili Sun Xueyan Liu Min Zhao a další

Zdroj: Future Internet, Vol 13, Iss 2, p 51 (2021)

Témata: neural networks, network representation learning, noninformative prior distribution, variational graph autoencoder, deep learning, Information technology, T58.5-58.64

Relation: https://www.mdpi.com/1999-5903/13/2/51; https://doaj.org/toc/1999-5903; https://doaj.org/article/cc2cb11b99f14c30a56a11f8911d2156

Dostupnost: https://doi.org/10.3390/fi13020051
https://doaj.org/article/cc2cb11b99f14c30a56a11f8911d2156