Výsledky vyhľadávania - "adversarial variational autoencoder"

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

Autori: 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

Autori: Sushil Kumar Maurya Dinesh Singh

Zdroj: Knowledge and Information Systems.

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

Autori: Qiyuan Xi Fei Wang Liangze Tao a ďalší

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

Distribution-Conditioned Adversarial Variational Autoencoder for Valid Instrumental Variable Generation

Autori: 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

Autori: Muhammad Usman Azka Rehman Abdullah Shahid a ďalší

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

Prístupová 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

Autori: Lixiao Cao Aoren Liu Zheng Qian a ďalší

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

Autori: Yunpeng Liu Hongkai Jiang Renhe Yao a ďalší

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

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

Autori: Hui Zhou Xin Liu Xiangju Li a ďalší

Zdroj: Applied Intelligence. 53:26750-26762

Speech Emotion Recognition based on Semi-Supervised Adversarial Variational Autoencoder

Autori: 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

Autori: Dequan Gao Meng Yang Bao Feng a ďalší

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

Wasserstein Adversarial Variational Autoencoder for Sequential Recommendation

Autori: Wenbiao Liu Xianjin Rong Yingli Zhong a ďalší

Zdroj: Lecture Notes in Computer Science ISBN: 9789819724208

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

Autori: Rehman, Abd Ur Rehman, Azka Usman, Muhammad a ďalší

Témy: 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

Autori: Usman, Muhammad Rehman, Azka Shahid, Abdullah a ďalší

Témy: 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

Autori: Zhou, Yadong Ding, Zhihao Liu, Xiaoming a ďalší

Zdroj: Neurocomputing. 483:105-115

Predmety: 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)

Prístupová 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

Autori: Ganghui Hu Youfang Lin Jing Wang a ďalší

Zdroj: Neurocomputing. 458:349-363

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

Prístupová 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

Autori: Laleh Najafizadeh Shiva Salsabilian

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

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

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

Semi-Supervised Adversarial Variational Autoencoder

Autori: Zemouri, Ryad

Prispievatelia: 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

Predmety: [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 súboru: application/pdf

Prístupová 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

Autori: Estermann, Benjamin Wattenhofer, Roger

Predmety: 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)

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

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

Autori: Mohadeseh Ghayekhloo Ahmad Nickabadi

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

Autori: Shiva Salsabilian Christian Lee David Margolis a ďalší

Zdroj: Journal of Neural Engineering. 21:036052

Predmety: 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

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