Výsledky vyhledávání - "Adversarial variational autoencoder"

Fault Detection and Identification of Underwater Thruster Without Fault Sample Based on Adversarial Variational Autoencoder

Autoři: Daqi Zhu Tianhong Zeng

Zdroj: IEEE Transactions on Industrial Electronics. :1-9

Deceptive reviewer group detection using self-adversarial variational autoencoder: a heterogeneous graph-based approach

Autoři: Sushil Kumar Maurya Dinesh Singh

Zdroj: Knowledge and Information Systems.

CM-AVAE: Cross-Modal Adversarial Variational Autoencoder for Visual-to-Tactile Data Generation

Autoři: Qiyuan Xi Fei Wang Liangze Tao a další

Zdroj: IEEE Robotics and Automation Letters. 9:5214-5221

Distribution-Conditioned Adversarial Variational Autoencoder for Valid Instrumental Variable Generation

Autoři: Xinshu Li Lina Yao

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence. 38:13664-13672

Advancing Metaverse-Based Healthcare With Multimodal Neuroimaging Fusion Via Multi-Task Adversarial Variational Autoencoder for Brain Age Estimation

Autoři: Muhammad Usman Azka Rehman Abdullah Shahid a další

Zdroj: IEEE Journal of Biomedical and Health Informatics. :1-9

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40030298

C-Gan-Vae: Causal Generative Adversarial Variational Autoencoder for Few Shot Fine Grained Cross Domain Fault Diagnosis for Planetary Gearbox

Autoři: Lixiao Cao Aoren Liu Zheng Qian a další

Interpretable data-augmented adversarial variational autoencoder with sequential attention for imbalanced fault diagnosis

Autoři: Yunpeng Liu Hongkai Jiang Renhe Yao a další

Zdroj: Journal of Manufacturing Systems. 71:342-359

Adversarial variational autoencoder for attributed graph embedding with high-frequency noise filtering

Autoři: Hui Zhou Xin Liu Xiangju Li a další

Zdroj: Applied Intelligence. 53:26750-26762

Speech Emotion Recognition based on Semi-Supervised Adversarial Variational Autoencoder

Autoři: Yufeng Xiao Yuqin Bo Zhiling Zheng

Zdroj: 2023 IEEE 10th International Conference on Cyber Security and Cloud Computing (CSCloud)/2023 IEEE 9th International Conference on Edge Computing and Scalable Cloud (EdgeCom). :275-280

Business systems KPI anomaly detection based on an adversarial variational autoencoder

Autoři: Dequan Gao Meng Yang Bao Feng a další

Zdroj: 2023 IEEE 3rd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). :1702-1706

Wasserstein Adversarial Variational Autoencoder for Sequential Recommendation

Autoři: Wenbiao Liu Xianjin Rong Yingli Zhong a další

Zdroj: Lecture Notes in Computer Science ISBN: 9789819724208

Biological Brain Age Estimation using Sex-Aware Adversarial Variational Autoencoder with Multimodal Neuroimages

Autoři: Rehman, Abd Ur Rehman, Azka Usman, Muhammad a další

Témata: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2412.05632

Multi-Task Adversarial Variational Autoencoder for Estimating Biological Brain Age with Multimodal Neuroimaging

Autoři: Usman, Muhammad Rehman, Azka Shahid, Abdullah a další

Témata: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2411.10100

Infer-AVAE: An attribute inference model based on adversarial variational autoencoder

Autoři: Zhou, Yadong Ding, Zhihao Liu, Xiaoming a další

Zdroj: Neurocomputing. 483:105-115

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Machine Learning (stat.ML), 02 engineering and technology, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/pdf/2012.15005
http://arxiv.org/abs/2012.15005

Self-adversarial variational autoencoder with spectral residual for time series anomaly detection

Autoři: Ganghui Hu Youfang Lin Jing Wang a další

Zdroj: Neurocomputing. 458:349-363

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/journals/ijon/ijon458.html#LiuLXHW21
https://doi.org/10.1016/j.neucom.2021.06.030
http://doi.org/10.1016/j.neucom.2021.06.030
https://www.sciencedirect.com/science/article/pii/S0925231221009346

An Adversarial Variational Autoencoder Approach Toward Transfer Learning for mTBI Identification

Autoři: Laleh Najafizadeh Shiva Salsabilian

Zdroj: 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER). :408-411

Témata: 03 medical and health sciences, 0302 clinical medicine, 0206 medical engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/ner/ner2021.html#SalsabilianN21

Semi-Supervised Adversarial Variational Autoencoder

Autoři: Zemouri, Ryad

Přispěvatelé: Zemouri, Ryad

Zdroj: Machine Learning and Knowledge Extraction, Vol 2, Iss 3, Pp 361-378 (2020)
Machine Learning and Knowledge Extraction
Volume 2
Issue 3
Pages 20-378

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], TK7885-7895, Computer engineering. Computer hardware, 0202 electrical engineering, electronic engineering, information engineering, artificial_intelligence_robotics, variational autoencoder, data generation, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], 02 engineering and technology, deep feature consistent, adversarial learning

Popis souboru: application/pdf

Přístupová URL adresa: https://www.mdpi.com/2504-4990/2/3/20/pdf
https://doaj.org/article/ee9bbbc5397b46549c2cc2bdd8ddde75
https://www.preprints.org/manuscript/202008.0051/v1
https://www.preprints.org/manuscript/202008.0051/v1/download
https://www.mdpi.com/2504-4990/2/3/20
https://www.mdpi.com/2504-4990/2/3/20/pdf
https://dblp.uni-trier.de/db/journals/make/make2.html#Zemouri20
https://hal-cnam.archives-ouvertes.fr/hal-02931571/document
https://hal-cnam.archives-ouvertes.fr/hal-02931571
https://cnam.hal.science/hal-02931571v1
https://doi.org/10.3390/make2030020
https://cnam.hal.science/hal-02931571v1/document

DAVA: Disentangling Adversarial Variational Autoencoder

Autoři: Estermann, Benjamin Wattenhofer, Roger

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, 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, 01 natural sciences, 0105 earth and related environmental sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2303.01384

GC-AVAE: A Graph Convolutional Adversarial Variational Autoencoder for Node Classification

Autoři: Mohadeseh Ghayekhloo Ahmad Nickabadi

An LSTM-based adversarial variational autoencoder framework for self-supervised neural decoding of behavioral choices

Autoři: Shiva Salsabilian Christian Lee David Margolis a další

Zdroj: Journal of Neural Engineering. 21:036052

Témata: 0301 basic medicine, Mice, 03 medical and health sciences, 0302 clinical medicine, Animals, Mice, Transgenic, Neural Networks, Computer, Supervised Machine Learning, Choice Behavior, Unsupervised Machine Learning

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38621379