Výsledky vyhledávání - supervised conditional variational autoencoder (VAE)

Structural Dynamics Feature Learning Using a Supervised Variational Autoencoder.

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

Zdroj: Journal of Engineering Mechanics. Feb2025, Vol. 151 Issue 2, p1-14. 14p.

Témata: *STRUCTURAL health monitoring, *WIND turbine blades, *AUTOENCODERS, *STRUCTURAL dynamics, *SUPERVISED learning

Language-Informed Hyperspectral Image Synthesis for Imbalanced-Small Sample Classification via Semi-Supervised Conditional Diffusion Model

Autoři: Zhu, Yimin Xu, Lincoln Linlin

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

URL: http://arxiv.org/abs/2502.19700

Prognosis prediction of patients with malignant pleural mesothelioma using conditional variational autoencoder on 3D PET images and clinical data.

Autoři: Matsuo, Hidetoshi Kitajima, Kazuhiro Kono, Atsushi K. a další

Zdroj: Medical Physics. Dec2023, Vol. 50 Issue 12, p7548-7557. 10p.

Témata: *POSITRON emission tomography computed tomography, *POSITRON emission tomography, *THREE-dimensional imaging, *DIAGNOSTIC imaging, *RECEIVER operating characteristic curves, *SURVIVAL analysis (Biometry), *STOCHASTIC learning models

Solving two-stage stochastic integer programs via representation learning

Autoři: WU, Yaoxin CAO, Zhiguang SONG, Wen a další

Zdroj: Research Collection School Of Computing and Information Systems

Témata: Conditional variational autoencoder, Contrastive learning, Semi-supervised learning, Stochastic integer programs, Artificial Intelligence and Robotics, Theory and Algorithms

Popis souboru: application/pdf

Relation: https://ink.library.smu.edu.sg/sis_research/10158; https://ink.library.smu.edu.sg/context/sis_research/article/11158/viewcontent/Two_StageStochasticInteger_av.pdf

Dostupnost: https://ink.library.smu.edu.sg/sis_research/10158
https://doi.org/10.1016/j.neunet.2025.107446
https://ink.library.smu.edu.sg/context/sis_research/article/11158/viewcontent/Two_StageStochasticInteger_av.pdf

Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs

Autoři: Lee, Dong Bok Lee, Seanie Jeong, Woo Tae a další

Témata: Computer Science - Computation and Language, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2005.13837

PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation

Autoři: Soumick Chatterjee Franziska Gaidzik Alessandro Sciarra a další

Zdroj: Medical image analysis 103, 103623 (2025). doi:10.1016/j.media.2025.103623

Témata: Observer Variation, FOS: Computer and information sciences, Conditional VAE, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, diagnostic imaging [Multiple Sclerosis], Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, methods [Image Interpretation, Computer-Assisted], Probabilistic UNet, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG), methods [Magnetic Resonance Imaging], Artificial Intelligence (cs.AI), Humans, Multiple sclerosis segmentation, ddc:610, Supervised Machine Learning, Distribution distance, Vessel segmentation, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40367700
http://arxiv.org/abs/2312.15686
https://pub.dzne.de/record/278930

Learning Sampling Distribution and Safety Filter for Autonomous Driving with VQ-VAE and Differentiable Optimization

Autoři: Idoko, Simon Sharma, Basant Singh, Arun Kumar

Témata: Computer Science - Robotics, text

URL: http://arxiv.org/abs/2403.19461

Chiller Fault Diagnosis Based on VAE-Enabled Generative Adversarial Networks.

Autoři: Yan, Ke Su, Jianye Huang, Jing a další

Zdroj: IEEE Transactions on Automation Science & Engineering. Jan2022, Vol. 19 Issue 1, p387-395. 9p.

Témata: *GENERATIVE adversarial networks, *DATA augmentation, *SUPERVISED learning, *ARTIFICIAL intelligence, *FAULT diagnosis

An Artificial Intelligence-Based Automatic Classifier for the Presence of False Lumen Thrombosis After Frozen Elephant Trunk Operation.

Autoři: Osswald, Anja Tsagakis, Konstantinos Thielmann, Matthias a další

Zdroj: Diagnostics (2075-4418); Dec2024, Vol. 14 Issue 24, p2853, 9p

Témata: ARTIFICIAL intelligence, CONVOLUTIONAL neural networks, AORTIC dissection, COMPUTED tomography, AUTOENCODERS

VAE-Info-cGAN: Generating Synthetic Images by Combining Pixel-level and Feature-level Geospatial Conditional Inputs

Autoři: Xiao, Xuerong Ganguli, Swetava Pandey, Vipul

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

URL: http://arxiv.org/abs/2012.04196

Automatic Classification of Magnetic Resonance Histology of Peripheral Arterial Chronic Total Occlusions Using a Variational Autoencoder: A Feasibility Study.

Autoři: Csore, Judit Karmonik, Christof Wilhoit, Kayla a další

Zdroj: Diagnostics (2075-4418); Jun2023, Vol. 13 Issue 11, p1925, 11p

Témata: CHRONIC total occlusion, MAGNETIC resonance, AUTOMATIC classification, PERIPHERAL vascular diseases, MAGNETIC resonance imaging

Loop closure detection of visual SLAM based on variational autoencoder.

Autoři: Shibin Song Fengjie Yu Xiaojie Jiang a další

Zdroj: Frontiers in Neurorobotics; 2024, p1-13, 13p

Témata: DEEP learning, IMAGE representation, HANDICRAFT

Swarm-Gen: Fast Generation of Diverse Feasible Swarm Behaviors

Autoři: Idoko, Simon Teja, B. Bhanu Krishna, K. Madhava a další

Témata: Computer Science - Robotics, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2501.19042

Conditional feature disentanglement learning for anomaly detection in machines operating under time-varying conditions

Autoři: Zhou, Haoxuan Lei, Zihao Zio, Enrico a další

Přispěvatelé: Zhou, Haoxuan Lei, Zihao Zio, Enrico a další

Zdroj: Mechanical Systems and Signal Processing. 191:110139

Témata: Feature disentanglement learning, Learning systems, [SPI] Engineering Sciences [physics], Anomaly detection, Variational autoencoder, 02 engineering and technology, Condition monitoring, [SPI]Engineering Sciences [physics], Bearing, Time-varying operating conditions, Machines, 0202 electrical engineering, electronic engineering, information engineering, [SHS.GESTION]Humanities and Social Sciences/Business administration, Feature extraction, [SHS.GESTION] Humanities and Social Sciences/Business administration

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/11311/1260306
https://doi.org/10.1016/j.ymssp.2023.110139
https://hal.science/hal-04103555v1
https://doi.org/10.1016/j.ymssp.2023.110139

Learning VAE with Categorical Labels for Generating Conditional Handwritten Characters

Autoři: Keita Goto Nakamasa Inoue

Zdroj: 2021 17th International Conference on Machine Vision and Applications (MVA). :1-5

Témata: 4. Education

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/mva/mva2021.html#GotoI21

EC-GAN: Emotion-Controllable GAN for Face Image Completion

Autoři: Yueqiao Chen Wenxia Yang Xi Fang a další

Zdroj: Applied Sciences, Vol 13, Iss 13, p 7638 (2023)

Témata: image completion, generative adversarial network, conditional variational autoencoder, facial emotion, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Relation: https://www.mdpi.com/2076-3417/13/13/7638; https://doaj.org/toc/2076-3417; https://doaj.org/article/7f6570922d7e4b4aa59a4d523a8ee392

Dostupnost: https://doi.org/10.3390/app13137638
https://doaj.org/article/7f6570922d7e4b4aa59a4d523a8ee392

VAESim: A probabilistic approach for self-supervised prototype discovery

Autoři: Ferrante, M Boccato, T Spasov, S a další

Přispěvatelé: Ferrante, M Boccato, T Spasov, S a další

Zdroj: Image and Vision Computing
Datacite
arXiv.org e-Print Archive

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Settore FIS/07, medical imaging, Computer Science - Computer Vision and Pattern Recognition, deep clustering, 02 engineering and technology, 3. Good health, Settore PHYS-06/A - Fisica per le scienze della vita, Machine Learning (cs.LG), prototypes discovery, variational autoencoders, 03 medical and health sciences, 0302 clinical medicine, Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, variational autoencoder, l'ambiente e i beni culturali, Computer Vision and Pattern Recognition

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2209.12279
https://hdl.handle.net/2108/340863
https://doi.org/10.1016/j.imavis.2023.104746

Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection

Autoři: Akrami, Haleh Joshi, Anand Aydore, Sergul a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2109.09374

Conditional Generative Denoising Autoencoder.

Autoři: Karatsiolis, Savvas Schizas, Christos N.

Zdroj: IEEE Transactions on Neural Networks & Learning Systems. Oct2020, Vol. 31 Issue 10, p4117-4129. 13p.

Témata: *MONTE Carlo method, *MARKOV chain Monte Carlo, SIGNAL denoising, SUPERVISED learning

VAE-Info-cGAN: generating synthetic images by combining pixel-level and feature-level geospatial conditional inputs

Autoři: Xuerong Xiao Swetava Ganguli Vipul Pandey

Zdroj: Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science. :1-10

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, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/pdf/2012.04196
http://arxiv.org/abs/2012.04196
https://arxiv.org/abs/2012.04196
http://arxiv.org/pdf/2012.04196.pdf
http://ui.adsabs.harvard.edu/abs/2020arXiv201204196X/abstract
https://dl.acm.org/doi/pdf/10.1145/3423457.3429361
https://dblp.uni-trier.de/db/journals/corr/corr2012.html#abs-2012-04196