Search Results - Temporal graph convolutional autoencoder

Temporal Graph Convolutional Autoencoder based Fault Detection for Renewable Energy Applications

Authors: Murshedul Arifeen Andrei Petrovski

Source: 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS). :1-6

Human-related anomalous event detection via spatial-temporal graph convolutional autoencoder with embedded long short-term memory network

Authors: Nanjun Li Faliang Chang Chunsheng Liu

Source: Neurocomputing. 490:482-494

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Spatio-Temporal Graph Convolutional Autoencoder for Transonic Wing Pressure Distribution Forecasting

Authors: Gabriele Immordino Andrea Vaiuso Andrea Da Ronch et al.

Source: Aerospace Science and Technology. 165:110516

Spatio-temporal graph convolutional autoencoder for transonic wing pressure distribution forecasting

Authors: Immordino, Gabriele Vaiuso, Andrea Da Ronch, Andrea et al.

File Description: text

Relation: https://eprints.soton.ac.uk/504263/1/1-s2.0-S1270963825005875-main.pdf; Immordino, Gabriele, Vaiuso, Andrea, Da Ronch, Andrea and Righi, Marcello (2025) Spatio-temporal graph convolutional autoencoder for transonic wing pressure distribution forecasting. Aerospace Science and Technology, 165, [110516]. (doi:10.1016/j.ast.2025.110516 ).

Availability: https://eprints.soton.ac.uk/504263/

A Spatio‐Temporal Enhanced Graph‐Transformer AutoEncoder embedded pose for anomaly detection

Authors: Honglei Zhu Pengjuan Wei Zhigang Xu

Source: IET Computer Vision, Vol 18, Iss 3, Pp 405-419 (2024)

Subject Terms: computer vision, convolutional neural nets, feature extraction, pose estimation, video surveillance, Computer applications to medicine. Medical informatics, R858-859.7, Computer software, QA76.75-76.765

File Description: electronic resource

Relation: https://doaj.org/toc/1751-9632; https://doaj.org/toc/1751-9640

Access URL: https://doaj.org/article/41d360b7678b4b1285f23c36b7d97b4f

Memory Enhanced Spatial-Temporal Graph Convolutional Autoencoder for Human-Related Video Anomaly Detection

Authors: Sibo Luo Shangshang Wang Yuan Wu et al.

Source: Lecture Notes in Computer Science ISBN: 9783031189128

DRDCAE-STGNN: An End-to-End Discrimina-tive Autoencoder with Spatio-Temporal Graph Learning for Motor Imagery Classification

Authors: Wang, Yi Zhang, Haodong Li, Hongqi

Subject Terms: Human-Computer Interaction, FOS: Computer and information sciences, Human-Computer Interaction (cs.HC)

Access URL: http://arxiv.org/abs/2509.05943

Rolling Bearing Fault Diagnosis via Temporal-Graph Convolutional Fusion.

Authors: Li, Fan Li, Yunfeng Wang, Dongfeng

Source: Sensors (14248220); Jul2025, Vol. 25 Issue 13, p3894, 19p

Subject Terms: FAULT diagnosis, FEATURE extraction, ROLLER bearings, GRAPH neural networks, CONVOLUTIONAL neural networks

Dataset for the paper 'Spatio-temporal Graph Convolutional Autoencoder for Transonic Wing Pressure Distribution Forecasting'

Authors: Immordino, Gabriele orcid:0000-0003-2718- Vaiuso, Andrea et al.

Contributors: Immordino, Gabriele orcid:0000-0003-2718- Vaiuso, Andrea et al.

Relation: https://zenodo.org/records/17129717; oai:zenodo.org:17129717; https://doi.org/10.5281/zenodo.17129717

Availability: https://doi.org/10.5281/zenodo.17129717
https://zenodo.org/records/17129717

Variable Structure Learning-Based Spatio-Temporal Graph Convolutional Networks for Chemical Process Quality Prediction with SHAP-Enhanced Interpretability.

Authors: Tang, Siyuan Zhu, Zheren Zhou, Yuanqiang et al.

Source: Processes; Nov2025, Vol. 13 Issue 11, p3751, 22p

Bidirectional Spatial–Temporal Graph Convolutional Model: Traffic Flow Forecasting With Enhanced Extended Capabilities.

Authors: Tan, Xiaogang Qian, Guoping Pei, Boyu et al.

Source: Journal of Advanced Transportation; 8/23/2025, Vol. 2025, p1-18, 18p

Subject Terms: INTELLIGENT transportation systems, SPATIOTEMPORAL processes, BOX-Jenkins forecasting, TRAFFIC flow measurement, TRAFFIC estimation, GEOSPATIAL data

A framework for continual learning in real-time traffic forecasting utilizing spatial–temporal graph convolutional recurrent networks.

Authors: Francies, Mariam Labib Khalil, Abeer Twakol Amer, Hanan M. et al.

Source: Complex & Intelligent Systems; Oct2025, Vol. 11 Issue 10, p1-28, 28p

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

Transient Stability Assessment of Power Systems Built upon Attention-Based Spatial–Temporal Graph Convolutional Networks.

Authors: Nan, Yu Niu, Weiping Chang, Yong et al.

Source: Energies (19961073); Jul2025, Vol. 18 Issue 14, p3824, 18p

Subject Terms: ELECTRIC power systems, GRAPH neural networks, MACHINE learning, SPATIOTEMPORAL processes, ELECTRIC power distribution grids, EMPIRICAL research, LOSS functions (Statistics), DYNAMIC stability

Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting.

Authors: Singh, Vandana Sahana, Sudip Kumar Bhattacharjee, Vandana

Source: Applied Sciences (2076-3417); Dec2024, Vol. 14 Issue 24, p11477, 18p

Subject Terms: CONVOLUTIONAL neural networks, GRAPH neural networks, TRAFFIC estimation, TIME series analysis, TRAFFIC patterns

基于多头注意力时空图卷积网络的交通事故预测. (Chinese)

Alternate Title: Traffic accident prediction based on multi-head attention spatio-temporal graph convolutional network. (English)

Authors: 姜天豪 王 瑞

Source: Journal of Shanghai University / Shanghai Daxue Xuebao; Aug2025, Vol. 31 Issue 4, p678-690, 13p

Subject Terms: SPATIAL ability, TRAFFIC accidents

GCN-Transformer Autoencoder with Knowledge Distillation for Unsupervised Video Anomaly Detection.

Authors: Yan, Mingchao Xiong, Yonghua She, Jinhua

Source: Journal of Advanced Computational Intelligence & Intelligent Informatics. May2025, Vol. 29 Issue 3, p659-667. 9p.

Subject Terms: *AUTOENCODERS, *TRANSFORMER models, *SCARCITY, *VIDEOS, *CLASSIFICATION

A Spatio‐Temporal Enhanced Graph‐Transformer AutoEncoder embedded pose for anomaly detection.

Authors: Zhu, Honglei Wei, Pengjuan Xu, Zhigang

Source: IET Computer Vision (Wiley-Blackwell); Apr2024, Vol. 18 Issue 3, p405-419, 15p

Subject Terms: TRANSFORMER models, INTRUSION detection systems (Computer security), HUMAN skeleton, COMPUTER vision, VIDEO surveillance, FEATURE extraction, ALGORITHMS

Spatial-temporal deep learning model based on Similarity Principle for dock shared bicycles ridership prediction

Authors: Jiahui Zhao Zhibin Li Pan Liu et al.

Source: Journal of Transport and Land Use, Vol 17, Iss 1 (2024)

Subject Terms: Transportation engineering, Keywords: Traffic demand prediction, Similarity-based Principle, Spatio-temporal Graph Convolutional Neural Network model, activity-based geographic information, prediction of bicycle sharing ridership, TA1001-1280, 0502 economics and business, 05 social sciences, Transportation and communications, HE1-9990

Access URL: https://doaj.org/article/912c74dba63f4108b6301fb6d75dafd7

STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

Authors: Tanmay Randhavane Rohan Chandra Uttaran Bhattacharya et al.

Source: Proceedings of the AAAI Conference on Artificial Intelligence. 34:1342-1350

Subject Terms: FOS: Computer and information sciences, Computer Science - Robotics, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Robotics (cs.RO)

Access URL: https://ojs.aaai.org/index.php/AAAI/article/download/5490/5346
http://arxiv.org/abs/1910.12906
https://arxiv.org/abs/1910.12906
http://ui.adsabs.harvard.edu/abs/2019arXiv191012906B/abstract
http://export.arxiv.org/pdf/1910.12906
https://arxiv.org/abs/1910.12906
https://dblp.uni-trier.de/db/conf/aaai/aaai2020.html#BhattacharyaMCR20
https://arxiv.org/pdf/1910.12906.pdf
http://dblp.uni-trier.de/db/journals/corr/corr1910.html#abs-1910-12906
https://ojs.aaai.org/index.php/AAAI/article/view/5490
https://aaai.org/ojs/index.php/AAAI/article/view/5490