Search Results - variational graph convolutional 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

Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders

Authors: Mishra, Aditya Samin, Ahnaf Mozib Etemad, Ali et al.

Index Terms: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2501.16626

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

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

Authors: Aabid Ahmad Mir Megat F. Zuhairi Shahrulniza Musa et al.

Source: Engineering, Technology & Applied Science Research. 15:19838-19847

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

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: noise robustness, Gas turbine, 0202 electrical engineering, electronic engineering, information engineering, MG-VAE, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, fault diagnosis, 01 natural sciences, TK1-9971, 0104 chemical sciences

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

Variational Graph Convolutional Networks for Dynamic Graph Representation Learning

Authors: Aabid A. Mir Megat F. Zuhairi Shahrulniza Musa et al.

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

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

Access URL: https://doaj.org/article/205888aa585544ec8d0e7f0c49e14058

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

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

Authors: Mir, Aabid Ahmad Zuhairi, Megat F. Musa, Shahrulniza et al.

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

Subject Terms: GRAPH neural networks, DEEP learning, CYBERTERRORISM, NEIGHBORHOODS, CLASSIFICATION

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; 2024, p1-14, 14p

Subject Terms: CONVOLUTIONAL neural networks, RANDOM forest algorithms, MICROBIAL biotechnology, DEEP learning

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

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

VGAE-Hub: a variational graph autoencoder framework for identifying shared hub genes in colorectal cancer and inflammatory bowel disease.

Authors: Joshi, Pratibha Verma, Ravi Singh, Buddha

Source: Network Modeling & Analysis in Health Informatics & Bioinformatics; 11/4/2025, Vol. 14 Issue 1, p1-18, 18p

A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction

Authors: Akyol, Gamze Sariel, Sanem Aksoy, Eren Erdal

Index Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Robotics, text

URL: http://arxiv.org/abs/2110.13280

Graph variational autoencoder with affinity propagation for community-aware anomaly detection in attributed networks.

Authors: Cao, Zhijie Yang, Chengkun Fan, Xiaoqing et al.

Source: Applied Soft Computing. Jan2026:Part D, Vol. 186, pN.PAG-N.PAG. 1p.

A new link prediction model for grain trade networks based on improved variational graph autoencoder and genetic algorithm.

Authors: Li, Yanhui Song, Yuzhi Yao, Qi et al.

Source: Applied Soft Computing. Aug2025, Vol. 180, pN.PAG-N.PAG. 1p.

Subject Terms: Grain trade, Genetic algorithms, Food security, Graph neural networks, Representations of graphs, Feature extraction

Dirichlet Graph Variational Autoencoder

Authors: Li, Jia Yu, Tomasyu Li, Jiajin et al.

Index Terms: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2010.04408

Multiview Variational Graph Autoencoders for Canonical Correlation Analysis

Authors: Kaloga, Yacouba Borgnat, Pierre Chepuri, Sundeep Prabhakar et al.

Index Terms: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2010.16132

Recommender systems based on variational autoencoders and graph convolutional neural networks

Authors: Kang, Peng

Thesis Advisors: Xue Liu (Internal/Supervisor)

Subject Terms: Computer Science

Relation: Pid: 161242

Availability: https://escholarship.mcgill.ca/concern/theses/g445cg72w

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

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

Index Terms: Diffusion process, graph neural networks (GNNs), spatiotemporal forecasting, variational graph autoencoders (VGAEs), Computer Sciences, Datavetenskap (datalogi), Article in journal, info:eu-repo/semantics/article, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-55718
IEEE Transactions on Neural Networks and Learning Systems, 2162-237X, 2025, 33:5, s. 9524-9537