Search Results - Graph convolutional and variational autoencoder

Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder

Authors: Jiang, Junhao Zuo, Yi Li, Zhiyuan

Source: Reliability Engineering and System Safety. 267

Subject Terms: Graph convolutional network, Trajectory prediction, Cooperative intention constructor, Intelligent situational awareness systems, Conditional variational autoencoder, Multi-modal interaction extractor

Access URL: https://research.chalmers.se/publication/549377

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

Authors: Murshedul Arifeen Andrei Petrovski Md Junayed Hasan et al.

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

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

File Description: electronic resource

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

Access URL: https://doaj.org/article/a68e9bb8f0bd42d6b8c9842c6321237e

Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatiotemporal Forecasting

Authors: Liang, Guojun, Postdoktor Tiwari, Prayag Nowaczyk, Sławomir et al.

Source: IEEE Transactions on Neural Networks and Learning Systems. 33(5):9524-9537

Subject Terms: Diffusion process, graph neural networks (GNNs), spatiotemporal forecasting, variational graph autoencoders (VGAEs)

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-55718
https://doi.org/10.1109/tnnls.2024.3415149

Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data

Authors: Seung-Hwan Choi Dawn An Inho Lee et al.

Source: Mathematics, Vol 12, Iss 23, p 3750 (2024)

Subject Terms: anomaly detection, graph convolutional network (GCN), variational autoencoder (VAE), statistical feature, probability-based anomaly score, Mathematics, QA1-939

File Description: electronic resource

Relation: https://www.mdpi.com/2227-7390/12/23/3750; https://doaj.org/toc/2227-7390

Access URL: https://doaj.org/article/c1d52f19b28848b1becfec82e190f2fb

Prediction of microbe–drug associations based on a modified graph attention variational autoencoder and random forest

Authors: Bo Wang Fangjian Ma Xiaoxin Du et al.

Source: Frontiers in Microbiology, Vol 15 (2024)

Subject Terms: microbe–drug association prediction, variational autoencoder, modified graph convolutional neural network, graph attention network, random forest classifier, computational prediction model, Microbiology, QR1-502

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fmicb.2024.1394302/full; https://doaj.org/toc/1664-302X

Access URL: https://doaj.org/article/5e963e31a3a540a0a7d0d21975537bff

Synergistic Integration of Image-Text Modalities in Telemedicine: VAE-Infused Graph Convolutional Networks for Diagnostic Decision-Making

Authors: Yirui Kuang Hui Jin Jiayu Yang et al.

Source: IEEE Access, Vol 13, Pp 63093-63107 (2025)

Subject Terms: Telemedicine, multimodal fusion, graph neural networks, variational autoencoders, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/10955270/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/9c3b4c47a53c4b2a87210659c816f623

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows

Authors: Jawahar, Pratik Aarrestad, Thea Chernyavskaya, Nadezda et al.

Subject Terms: Data Management and Data Science, Information and Computing Sciences, Information Systems, anomaly detection, variational auto encoder, normalizing flow, Large Hadron Collider, new physics beyond standard model, graph convolutional network, convolutional neural net, Data management and data science, Information systems

File Description: application/pdf

Access URL: https://escholarship.org/uc/item/9d87s2q3
https://escholarship.org/content/qt9d87s2q3/qt9d87s2q3.pdf

VHGAE: Drug-Target Interaction Prediction Model Based on Heterogeneous Graph Variational Autoencoder.

Authors: Zhang C Sun J Xing L et al.

Source: Interdisciplinary sciences, computational life sciences [Interdiscip Sci] 2025 Aug 21. Date of Electronic Publication: 2025 Aug 21.

Publication Type: Journal Article

Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101515919 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1867-1462 (Electronic) Linking ISSN: 18671462 NLM ISO Abbreviation: Interdiscip Sci Subsets: MEDLINE

Graph convolutional network based on self-attention variational autoencoder and capsule contrastive learning for aspect-based sentiment analysis.

Authors: Wang, Xinyue Liu, Long Chen, Zhuo et al.

Source: Expert Systems with Applications. Jun2025, Vol. 279, pN.PAG-N.PAG. 1p.

Subject Terms: *CAPSULE neural networks, *AUTOENCODERS, *SENTIMENT analysis, *SOURCE code, *LEARNING modules

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

Authors: Arifeen, Murshedul Petrovski, Andrei Hasan, Md Junayed et al.

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

Subject Terms: SOLAR cells, RENEWABLE energy sources, PHOTOVOLTAIC power systems, SOLAR energy, AUTOENCODERS

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

Authors: Xuan, Ping Fan, Mengsi Cui, Hui et al.

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

Subject Terms: *PROTEIN-protein interactions, *CONVOLUTIONAL neural networks, *PROTEIN drugs

Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data.

Authors: Choi, Seung-Hwan An, Dawn Lee, Inho et al.

Source: Mathematics (2227-7390); Dec2024, Vol. 12 Issue 23, p3750, 16p

Subject Terms: INDUSTRIAL robots, ANOMALY detection (Computer security), AUTOENCODERS, SYSTEM failures, FEATURE extraction, DEEP learning

VAE-GCN: Deep Graph Convolutional Network via Variational Autoencoder for Multivariable Time Series Classification

Authors: Li, Lu Wu, Gongqing

Source: Lecture Notes in Computer Science ; Advanced Intelligent Computing Technology and Applications ; page 199-210 ; ISSN 0302-9743 1611-3349 ; ISBN 9789819698806 9789819698813

Availability: https://doi.org/10.1007/978-981-96-9881-3_17
https://link.springer.com/content/pdf/10.1007/978-981-96-9881-3_17

Enhancing Gas Turbine Fault Diagnosis Using a Multi-Scale Dilated Graph Variational Autoencoder Model

Authors: Zhang Kun Li Hongren Wang Xin et al.

Source: IEEE Access, Vol 12, Pp 104818-104832 (2024)

Subject Terms: Gas turbine, fault diagnosis, MG-VAE, noise robustness, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/10613765/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/c986c7c9e0e34b09bbf948eb168f8205

HHGNN: Hyperbolic Hypergraph Convolutional Neural Network based on variational autoencoder.

Authors: Mei, Zhangyu Bi, Xiao Wen, Yating et al.

Source: Neurocomputing. Oct2024, Vol. 601, pN.PAG-N.PAG. 1p.

Subject Terms: *CONVOLUTIONAL neural networks, *GRAPH neural networks, *HYPERBOLIC spaces, *REPRESENTATIONS of graphs, *DIAGNOSIS of diabetes

Graph Representation Learning on Street Networks.

Authors: Neira, Mateo Murcio, Roberto

Source: ISPRS International Journal of Geo-Information; Aug2025, Vol. 14 Issue 8, p284, 18p

Subject Terms: REPRESENTATIONS of graphs, URBAN morphology, PATTERN perception, SPATIAL behavior, LATENT variables, ROAD construction, TRAFFIC patterns, CONVOLUTIONAL neural networks

Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion

Authors: Bourached, Anthony Gray, Robert Guan, Xiaodong et al.

Index Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Mathematics - Probability, text

URL: http://arxiv.org/abs/2111.12602

scVGAE: A Novel Approach using ZINB-Based Variational Graph Autoencoder for Single-Cell RNA-Seq Imputation

Authors: Inoue, Yoshitaka

Index Terms: Quantitative Biology - Genomics, Computer Science - Computational Engineering, Finance, and Science, text

URL: http://arxiv.org/abs/2403.08959

VGE: Gene-Disease Association by Variational Graph Embedding

Authors: Peng Han Xiangliang Zhang

Source: International Journal of Crowd Science, Vol 8, Iss 2, Pp 95-99 (2024)

Subject Terms: disease-gene association, graph convolutional network (gcn), variational antoencoder (vae), Technology, Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: https://www.sciopen.com/article/10.26599/IJCS.2024.9100004; https://doaj.org/toc/2398-7294

Access URL: https://doaj.org/article/433f523c1b194c51bb094eaeb00d9154

Frequency-Quantized Variational Autoencoder Based on 2D-FFT for Enhanced Image Reconstruction and Generation.

Authors: Feng, Jianxin Liu, Xiaoyao

Source: Computers, Materials & Continua; 2025, Vol. 83 Issue 2, p2087-2107, 21p

Subject Terms: IMAGE reconstruction, AUTOENCODERS, PERCEPTUAL learning, FAST Fourier transforms