Výsledky vyhledávání - variational graph conventional autoencoder

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays

Autoři: Murshedul Arifeen Andrei Petrovski Md Junayed Hasan a další

Zdroj: Machines, Vol 12, Iss 12, p 894 (2024)

Témata: solar array, photovoltaic array, fault detection, fault diagnosis, graph convolutional network, variational autoencoder, Mechanical engineering and machinery, TJ1-1570

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2075-1702/12/12/894; https://doaj.org/toc/2075-1702

Přístupová URL adresa: https://doaj.org/article/a68e9bb8f0bd42d6b8c9842c6321237e

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays.

Autoři: Arifeen, Murshedul Petrovski, Andrei Hasan, Md Junayed a další

Zdroj: Machines; Dec2024, Vol. 12 Issue 12, p894, 15p

Témata: SOLAR cells, RENEWABLE energy sources, PHOTOVOLTAIC power systems, SOLAR energy, AUTOENCODERS

MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data.

Autoři: Zhao J He J Guan P a další

Zdroj: Analytical chemistry [Anal Chem] 2025 Oct 28; Vol. 97 (42), pp. 23222-23233. Date of Electronic Publication: 2025 Oct 19.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: American Chemical Society Country of Publication: United States NLM ID: 0370536 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1520-6882 (Electronic) Linking ISSN: 00032700 NLM ISO Abbreviation: Anal Chem Subsets: MEDLINE

Výrazy ze slovníku MeSH: Data Mining* , Deep Learning*, Humans ; Autoencoder

Graph-Embedded Neural Architecture Search: A Variational Approach for Optimized Model Design.

Autoři: Hemmi, Kazuki Tanigaki, Yuki Hara, Kaisei a další

Zdroj: Computers, Materials & Continua; 2025, Vol. 84 Issue 2, p2245-2271, 27p

Témata: GRAPH neural networks, DEEP learning, ARTIFICIAL intelligence, MACHINE learning, EXPERTISE

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

Autoři: Mingye Wang Xiaohui Hu Pan Xie a další

Zdroj: Information Technology & Control; 2024, Vol. 53 Issue 2, p570-583, 14p

Témata: LANGUAGE models, LEARNING strategies, GRAPH neural networks, RECOMMENDER systems, BIPARTITE graphs

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

Autoři: Liu, Lijun Wu, Xiaoyang Yu, Jun a další

Zdroj: Biology (2079-7737); Sep2024, Vol. 13 Issue 9, p713, 15p

Témata: ARTIFICIAL neural networks, RNA sequencing, SCALABILITY, HETEROGENEITY

A Transductive Zero-Shot Learning Framework for Ransomware Detection Using Malware Knowledge Graphs.

Autoři: Wang, Ping Li, Hao-Cyuan Lin, Hsiao-Chung a další

Zdroj: Information. Jun2025, Vol. 16 Issue 6, p458. 35p.

Témata: Knowledge graphs, Receiver operating characteristic curves, Deep learning, Behavioral assessment, Autoencoder

Enhanced Variational Graph Convolutional Networks with Multi-Scale Convolutions and Attention Mechanisms for Dynamic Network Analysis.

Autoři: Mir, Aabid Ahmad Zuhairi, Megat F. Musa, Shahrulniza a další

Zdroj: Engineering, Technology & Applied Science Research; Feb2025, Vol. 15 Issue 1, p19838-19847, 10p

Témata: GRAPH neural networks, DEEP learning, CYBERTERRORISM, NEIGHBORHOODS, CLASSIFICATION

Variational Graph Convolutional Networks for Dynamic Graph Representation Learning

Autoři: Aabid A. Mir Megat F. Zuhairi Shahrulniza Musa a další

Zdroj: IEEE Access, Vol 12, Pp 161697-161717 (2024)

Témata: network security, deep learning, graph neural networks, Anomaly detection, complex networks, Electrical engineering. Electronics. Nuclear engineering, heterogeneous networks, TK1-9971

Přístupová URL adresa: https://doaj.org/article/205888aa585544ec8d0e7f0c49e14058

A Wi-Fi Fingerprinting Indoor Localization Framework Using Feature-Level Augmentation via Variational Graph Auto-Encoder.

Autoři: Kim, Dongdeok Park, Jae-Hyeon Suh, Young-Joo

Zdroj: Electronics (2079-9292); Jul2025, Vol. 14 Issue 14, p2807, 19p

Témata: DATA augmentation, INDOOR positioning systems, WIRELESS geolocation systems, GRAPH neural networks, MACHINE learning, MULTIPLE imputation (Statistics)

MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.

Autoři: Wang, Feng Chu, Jinming Shen, Liyan a další

Zdroj: BMC Biology; 8/11/2025, Vol. 23 Issue 1, p1-24, 24p

Témata: PROTEIN-protein interactions, DEEP learning, LANGUAGE models, GRAPH neural networks, BIOINFORMATICS, SACCHAROMYCES cerevisiae

DCMF-PPI: a protein-protein interaction predictor based on dynamic condition and multi-feature fusion.

Autoři: Chen, Siqi Zheng, Anhong Yu, Weichi a další

Zdroj: BMC Bioinformatics; 10/15/2025, Vol. 26 Issue 1, p1-27, 27p

Témata: PROTEIN-protein interactions, DYNAMIC models, CONVOLUTIONAL neural networks, MOLECULAR dynamics, GRAPH neural networks

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

Alternate Title: Autocodificadores de grafos isomorfos versus firmados para la reconstrucción de redes de polimorfismos de un solo nucleótido de microARN en paisajes osteogenómicos periodontales. (Spanish)

Autoři: Sharma, Sarvagya Yadalam, Pradeep Kumar Ardila, Carlos M.

Zdroj: Gaceta Médica de Caracas; jul-sep2025, Vol. 133 Issue 3, p675-685, 11p

MPI-VGAE: protein–metabolite enzymatic reaction link learning by variational graph autoencoders.

Autoři: Wang, Cheng Yuan, Chuang Wang, Yahui a další

Zdroj: Briefings in Bioinformatics; Jul2023, Vol. 24 Issue 4, p1-12, 12p

Témata: DEEP learning, ALZHEIMER'S disease, ETIOLOGY of diseases, MACHINE learning, MOLECULAR docking, COLORECTAL cancer

Causal Structure Representation Learning of Unobserved Confounders in Latent Space for Recommendation.

Autoři: Xu, Hangtong Xu, Yuanbo Li, Chaozhuo a další

Zdroj: ACM Transactions on Information Systems. Nov2025, Vol. 43 Issue 6, p1-29. 29p.

Témata: *Recommender systems, Causal models, Weather, Noise

GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug–protein interaction prediction.

Autoři: Xuan, Ping Fan, Mengsi Cui, Hui a další

Zdroj: Briefings in Bioinformatics. Jan2022, Vol. 23 Issue 1, p1-12. 12p.

Témata: PROTEIN-protein interactions, CONVOLUTIONAL neural networks, PROTEIN drugs

DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads.

Autoři: Song, Kailu Zheng, Yumin Zhao, Bowen a další

Zdroj: Nature Communications; 7/4/2025, Vol. 16 Issue 1, p1-26, 26p

Variational graph neural network with diffusion prior for link prediction: Variational graph neural network with diffusion...: F.F. Vladimir et al.

Autoři: Su, Hailong Li, Zhipeng Yuan, Chang-An a další

Zdroj: Applied Intelligence; Jan2025, Vol. 55 Issue 2, p1-14, 14p

Témata: GRAPH neural networks, LATENT variables, GAUSSIAN distribution, MULTILAYERS, NOISE

TV-CCANM: a transformer variational inference in confounding cascade additive noise model for causal effect estimation.

Autoři: Ahmad, Sohail Wang, Hong

Zdroj: Journal of Statistical Computation & Simulation. Sep2025, Vol. 95 Issue 14, p3048-3076. 29p.

Témata: CAUSAL inference, CAUSAL models

Adaptive Sparsified Graph Learning Framework for Vessel Behavior Anomalies

Autoři: Kim, Jeehong Kim, Minchan Ju, Jaeseong a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2502.14197