Výsledky vyhledávání - Supervised variational autoencoder

A supervised variational autoencoder framework for dimensionality reduction and predictive modeling in high-dimensional socioeconomic data

Autoři: Pei Xue Tianshun Li

Zdroj: Journal of Economy and Technology, Vol 4, Iss, Pp 9-19 (2026)

Témata: High-dimensional data, Socioeconomic forecasting, Economics as a science, Electronic computers. Computer science, Supervised variational autoencoder, Social Sciences, QA75.5-76.95, Dimensionality reduction, HB71-74, Nonlinear representation learning, Predictive modeling

Přístupová URL adresa: https://doaj.org/article/38a6a8d09a8045ceaf6f58f757d3bf5e

A Semi-Supervised Variational Autoencoder for Fault Detection of Low-Severity Inter-Turn Short-Circuit in PMSMs

Autoři: Mingda Zhu Du Nguyen Peihua Han a další

Zdroj: 2025 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD). :1-6

Noise-Aware Self-Supervised Variational Autoencoder for Speech Enhancement

Autoři: Amogh Dixit K. S. Nataraj Nitya Tiwari

Zdroj: Circuits, Systems, and Signal Processing. 44:5010-5043

Efficient few-shot medical image segmentation via self-supervised variational autoencoder.

Autoři: Zhou Y Zhou F Xi F a další

Zdroj: Medical image analysis [Med Image Anal] 2025 Aug; Vol. 104, pp. 103637. Date of Electronic Publication: 2025 May 26.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 9713490 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1361-8423 (Electronic) Linking ISSN: 13618415 NLM ISO Abbreviation: Med Image Anal Subsets: MEDLINE

Výrazy ze slovníku MeSH: Supervised Machine Learning* , Image Processing, Computer-Assisted*/methods , Image Interpretation, Computer-Assisted*/methods , Magnetic Resonance Imaging*, Humans ; Algorithms ; Autoencoder

A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network

Autoři: Yuanyuan Qu Tao Li Shichen Fu a další

Zdroj: Nonlinear Dynamics. 113:459-478

Semi-Supervised Variational Autoencoder for Cell Feature Extraction In Multiplexed Immunofluorescence Images

Autoři: Sandarenu, Piumi Chen, Julia Slapetova, Iveta a další

Zdroj: 2024 IEEE International Symposium on Biomedical Imaging (ISBI). :1-5

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, 3. Good health

Přístupová URL adresa: http://arxiv.org/abs/2406.15727

Structural Dynamics Feature Learning Using a Supervised Variational Autoencoder

Autoři: Kiran Bacsa Wei Liu Imad Abdallah a další

Zdroj: Journal of Engineering Mechanics. 151

Structural Dynamics Feature Learning Using a Supervised Variational Autoencoder

Autoři: Bacsa, Kiran Liu, Wei Abdallah, Imad a další

Zdroj: Journal of Engineering Mechanics, 151 (2)

Popis souboru: application/application/pdf

Přístupová URL adresa: http://hdl.handle.net/20.500.11850/710877

Predicting Fetal Outcomes from Cardiotocography Signals Using a Supervised Variational Autoencoder

Autoři: Tolladay, John Albert, Beth Jones, Gabriel Davis

Témata: Machine Learning, FOS: Computer and information sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2509.06540

Label Noise Robust Image Representation Learning Based on Supervised Variational Autoencoders in Remote Sensing

Autoři: Sumbul, Gencer Demir, Begüm

Zdroj: International Geoscience and Remote Sensing Symposium
IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

Přístupová URL adresa: http://arxiv.org/abs/2306.08575

Self-Supervised Variational Autoencoder for Unsupervised Object Counting from Very-High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas

Autoři: Gella, Getachew Workineh Gangloff, Hugo Wendt, Lorenz a další

Přispěvatelé: Gella, Getachew Workineh Gangloff, Hugo Wendt, Lorenz a další

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 62:1-18

Témata: 15. Life on land, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

Přístupová URL adresa: https://eplus.uni-salzburg.at/id/9453423
https://doi.org/10.1109/tgrs.2023.3345179

Customization of latent space in semi-supervised Variational AutoEncoder

Autoři: Seunghwan An Jong-June Jeon

Zdroj: Pattern Recognition Letters. 177:54-60

Self-supervised variational autoencoder towards recommendation by nested contrastive learning

Autoři: Jing Wang Jun Wu Caiyan Jia a další

Zdroj: Applied Intelligence. 53:18887-18897

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

Using Semi‐supervised Variational Autoencoder and Acute fMRI Changes to Predict Antidepressant Treatment Responses Among Older Adults with Depression

Autoři: Linghai Wang Jihui Lee Akiko Mizuno a další

Zdroj: Alzheimer's & Dementia. 19

Témata: 03 medical and health sciences, 0302 clinical medicine, 3. Good health

A Joint Semi-Supervised Variational Autoencoder and Transfer Learning Model for Designing Molecular Transition Metal Complexes

Autoři: Tzuhsiung Yang Tzu-Hang Lee Yu-Ting Chen a další

Self-supervised Variational Autoencoder for Recommender Systems

Autoři: Jing Wang Gangdu Liu Jun Wu a další

Zdroj: 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). :831-835

Early detection and diagnosis of wind turbine abnormal conditions using an interpretable supervised variational autoencoder model

Autoři: Oliveira-Filho, Adaiton Zemouri, Ryad Cambron, Philippe a další

Témata: Article publié dans une revue, révisé par les pairs, Non évalué par les pairs

URL: https://espace2.etsmtl.ca/id/eprint/27099/
https://espace2.etsmtl.ca/id/eprint/27099
http://dx.doi.org/10.3390/en16124544
10.3390/en16124544

Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder

Autoři: Yi Yang Fan Zhou Shengming Zhang

Zdroj: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. :846-852

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

Přístupová URL adresa: https://www.aclweb.org/anthology/2020.acl-main.78.pdf

Early Detection and Diagnosis of Wind Turbine Abnormal Conditions Using an Interpretable Supervised Variational Autoencoder Model

Autoři: Adaiton Oliveira-Filho Ryad Zemouri Philippe Cambron a další

Zdroj: Energies, Vol 16, Iss 12, p 4544 (2023)

Témata: wind turbine, condition monitoring, variational autoencoder, SCADA data, early detection, diagnosis, Technology

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1996-1073/16/12/4544; https://doaj.org/toc/1996-1073

Přístupová URL adresa: https://doaj.org/article/44a9ca5e1aaf47ba9cf93e60ffa37933

Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencoder

Autoři: Wu, Chuhan Wu, Fangzhao Qi, Tao a další

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2204.00536