Výsledky vyhledávání - variational graph convolutional autoencoder

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

Autoři: Jiang, Junhao Zuo, Yi Li, Zhiyuan

Zdroj: Reliability Engineering and System Safety. 267

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

Přístupová URL adresa: https://research.chalmers.se/publication/549377

Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders

Autoři: Mishra, Aditya Samin, Ahnaf Mozib Etemad, Ali a další

Témata: 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

Autoři: Liang, Guojun, Postdoktor Tiwari, Prayag Nowaczyk, Sławomir a další

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

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

Popis souboru: print

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

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

Autoři: Jawahar, Pratik Aarrestad, Thea Chernyavskaya, Nadezda a další

Témata: 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

Popis souboru: application/pdf

Přístupová URL adresa: 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

Autoři: Zhang Kun Li Hongren Wang Xin a další

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

Témata: 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

Přístupová URL adresa: https://doaj.org/article/c986c7c9e0e34b09bbf948eb168f8205

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

Autoři: Inoue, Yoshitaka

Témata: 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.

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

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

Autoři: Bo Wang Fangjian Ma Xiaoxin Du a další

Zdroj: Frontiers in Microbiology; 2024, p1-14, 14p

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

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

Autoři: Bourached, Anthony Gray, Robert Guan, Xiaodong a další

Témata: 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.

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

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

Autoři: Joshi, Pratibha Verma, Ravi Singh, Buddha

Zdroj: 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

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

Témata: 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.

Autoři: Cao, Zhijie Yang, Chengkun Fan, Xiaoqing a další

Zdroj: 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.

Autoři: Li, Yanhui Song, Yuzhi Yao, Qi a další

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

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

Dirichlet Graph Variational Autoencoder

Autoři: Li, Jia Yu, Tomasyu Li, Jiajin a další

Témata: Computer Science - Machine Learning, text

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

Multiview Variational Graph Autoencoders for Canonical Correlation Analysis

Autoři: Kaloga, Yacouba Borgnat, Pierre Chepuri, Sundeep Prabhakar a další

Témata: Computer Science - Machine Learning, Statistics - Machine Learning, text

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

A novel intelligent multicross domain fault diagnosis of servo motor-bearing system based on Domain Generalized Graph Convolution Autoencoder.

Autoři: Zhao, Xiaoli Hu, Yuanhao Liu, Jiahui a další

Zdroj: Structural Health Monitoring; May2025, Vol. 24 Issue 3, p1485-1499, 15p

Témata: AUTOENCODERS, FAULT diagnosis, DEEP learning, REPRESENTATIONS of graphs, ROLLER bearings

Recommender systems based on variational autoencoders and graph convolutional neural networks

Autoři: Kang, Peng

Thesis Advisors: Xue Liu (Internal/Supervisor)

Témata: Computer Science

Relation: Pid: 161242

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

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

Autoři: Liang, Guojun Tiwari, Prayag Nowaczyk, Sławomir a další

Témata: 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

Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks

Autoři: Salha, Guillaume Hennequin, Romain Vazirgiannis, Michalis

Témata: Computer Science - Machine Learning, Computer Science - Social and Information Networks, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/1910.00942