Suchergebnisse - Semi-supervised variational autoencoder~

Fault diagnosis of power equipment based on variational autoencoder and semi‐supervised learning von Ye, Bo, Li, Feng, Zhang, Linghao, Chang, Zhengwei, Wang, Bin, Zhang, Xiaoyu, Bodanbai, Sayina

“… ) method based on variational autoencoder and semi‐supervised learning is proposed in this paper …”
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Customization of latent space in semi-supervised Variational AutoEncoder von An, Seunghwan, Jeon, Jong-June

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Exploring semi-supervised variational autoencoders for biomedical relation extraction von Zhang, Yijia, Lu, Zhiyong

“… •A semi-supervised method is proposed based on variational autoencoders (VAE) for biomedical relation extraction …”
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Learning from small medical data—robust semi-supervised cancer prognosis classifier with Bayesian variational autoencoder von Hsu, Te-Cheng, Lin, Che

“… Results We propose a robust Semi-supervised Cancer prognosis classifier with bAyesian variational autoeNcoder (SCAN …”
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A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network von Qu, Yuanyuan, Li, Tao, Fu, Shichen, Wang, Zhisheng, Chen, Jian, Zhang, Yupeng

“… A mechanical fault diagnosis model with Semi-Supervised Variational Autoencoder based on Long Short-Term Memory network (LSTM-SSVAE …”
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Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders von Whiteway, Matthew R., Biderman, Dan, Friedman, Yoni, Dipoppa, Mario, Buchanan, E. Kelly, Wu, Anqi, Zhou, John, Bonacchi, Niccolò, Miska, Nathaniel J., Noel, Jean-Paul, Rodriguez, Erica, Schartner, Michael, Socha, Karolina, Urai, Anne E., Salzman, C. Daniel, Cunningham, John P., Paninski, Liam

“… Recent neuroscience studies demonstrate that a deeper understanding of brain function requires a deeper understanding of behavior. Detailed behavioral …”
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Developing semi-supervised variational autoencoder-generative adversarial network models to enhance quality prediction performance von Ooi, Sai Kit, Tanny, Dave, Chen, Junghui, Wang, Kai

“… Such discrepancy exists because of the time lag for obtaining quality data. This paper proposes semi-supervised variational autoencoder-generative adversarial network (S2-VAE/GAN …”
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Semi-supervised Variational Autoencoder for WiFi Indoor Localization von Chidlovskii, Boris, Antsfeld, Leonid

“… We address the problem of indoor localization based on WiFi signal strengths. We develop a semi-supervised deep learning method able to train a prediction model …”
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Semi-Supervised Adversarial Variational Autoencoder von Zemouri, Ryad

“… We present a method to improve the reconstruction and generation performance of a variational autoencoder (VAE …”
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R/C buildings’ seismic damage prediction based on semi-supervised automatic differentiation variational inference deep autoencoder von Demertzis, K, Kostinakis, K, Morfidis, K, Iliadis, L

“… Structural damage from earthquakes has been assessed using a variety of methodologies, both statistical and, more recently, utilizing Machine Learning (ML) …”
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Semi-Supervised Variational Autoencoders for Out-of-Distribution Generation von Lavda, Frantzeska, Kalousis, Alexandros

“… ) data in a semi-supervised manner. Unlike previous approaches that use new factors of variation during testing, our method uses only existing attributes from the training data but in ways that were not seen during training (e.g., small objects of a specific shape during training and large objects of the same shape during testing) …”
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Semi-supervised Variational Autoencoders for Regression: Application to Soft Sensors von Zhuang, Yilin, Zhou, Zhuobin, Alakent, Burak, Mercangoz, Mehmet

“… We present the development of a semi-supervised regression method using variational autoencoders (VAE …”
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Infinite Variational Autoencoder for Semi-Supervised Learning von Abbasnejad, M. Ehsan, Dick, Anthony, van den Hengel, Anton

“… This paper presents an infinite variational autoencoder (VAE) whose capacity adapts to suit the input data …”
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Semi-Supervised Variational Autoencoder for Cell Feature Extraction In Multiplexed Immunofluorescence Images von Sandarenu, Piumi, Chen, Julia, Slapetova, Iveta, Browne, Lois, Graham, Peter H., Swarbrick, Alexander, Millar, Ewan K.A., Song, Yang, Meijering, Erik

“… We propose a deep learning-based cell feature extraction model using a variational autoencoder with supervision using a latent subspace to extract cell features in mIF images …”
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A Semi-supervised Gaussian Mixture Variational Autoencoder method for few-shot fine-grained fault diagnosis von Zhao, Zhiqian, Xu, Yeyin, Zhang, Jiabin, Zhao, Runchao, Chen, Zhaobo, Jiao, Yinghou

“… To tackle those issue, we propose a novel semi-supervised Gaussian Mixed Variational Autoencoder method, SeGMVAE, aimed at acquiring unsupervised representations that can be transferred across fine …”
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Semi-Supervised Deep Conditional Variational Autoencoder for Soft Sensor Modeling von Tang, Xiaochu, Yan, Jiawei, Li, Yuan, Zhang, Xinmin, Song, Zhihuan

“… Variational autoencoder (VAE) as an unsupervised deep generated model has been widely applied to process modeling for industrial processes due to its excellent ability in nonlinear and uncertain feature extraction …”
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DAS-Accelerometer Data Fusion With Semi-Supervised Graph Variational Autoencoder for In-Service Train Wheel Flat Detection von Dong, Yiqing, Han, Chengjia, Qu, Shuai, Zhao, Chaoyang, Madan, Aayush, Fu, Yuguang, Yang, Yaowen

“… To address these issues, this study introduces a semi-supervised learning workflow integrating multi-sensor data from Distributed Acoustic Sensing (DAS …”
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SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases von Namba, Satoko, Li, Chen, Yuyama Otani, Noriko, Yamanishi, Yoshihiro

“… rare diseases, intractable diseases). Results This study presents a novel machine learning approach using multimodal vector-quantized variational autoencoders (VQ-VAEs …”
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Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets von Wang, Zihao, Wu, Zeyu, Deng, Minghua

“… To address these challenges, we proposes a flexible integration framework based on Variational Autoencoder called scGCM …”
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Semi-Supervised Channel Equalization Using Variational Autoencoders von Burshtein, David, Bery, Eli

“… We present methods for semi-supervised learning (SSL) from few pilots over nonlinear channels using variational autoencoders …”
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