Search Results - Bayesian autoencoder

Learning from small medical data—robust semi-supervised cancer prognosis classifier with Bayesian variational autoencoder by Hsu, Te-Cheng, Lin, Che

“… Results We propose a robust Semi-supervised Cancer prognosis classifier with bAyesian variational autoeNcoder (SCAN…”
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In-situ sensor calibration in an operational air-handling unit coupling autoencoder and Bayesian inference by Yoon, Sungmin

“…).•An advanced in-situ sensor calibration method is proposed by coupling autoencoder and Bayesian inference…”
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Revisiting Bayesian Autoencoders With MCMC by Chandra, Rohitash, Jain, Mahir, Maharana, Manavendra, Krivitsky, Pavel N.

“… This has been addressed with variational autoencoders so far. Bayesian inference via Markov Chain Monte Carlo (MCMC…”
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Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection by Yong, Bang Xiang, Brintrup, Alexandra

“… Therefore, in this work, the formulation of Bayesian autoencoders (BAEs) is adopted to quantify the total anomaly uncertainty, comprising epistemic and aleatoric uncertainties…”
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Probabilistic occupancy forecasting for risk-aware optimal ventilation through autoencoder Bayesian deep neural networks by Zhuang, Chaoqun, Choudhary, Ruchi, Mavrogianni, Anna

“… This study, therefore, proposes an autoencoder Bayesian Long Short-term Memory neural network (LSTM…”
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Variational autoencoder Bayesian matrix factorization (VABMF) for collaborative filtering by Aldhubri, Ali, Lasheng, Yu, Mohsen, Farida, Al-Qatf, Majjed

“… An alternative approach to PMF is a Bayesian PMF model that suggests the Markov chain Monte Carlo algorithm as a full estimation for approximate intractable posterior over model parameters…”
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Two-step hybrid collaborative filtering using deep variational Bayesian autoencoders by Nahta, Ravi, Meena, Yogesh Kumar, Gopalani, Dinesh, Chauhan, Ganpat Singh

“… the latent vector representations when users or items are added to the underlying dataset. To address these issues, we propose a two-step hybrid variational Bayesian autoencoder to characterize the uncertainty of predicted ratings…”
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Coalitional Bayesian autoencoders: Towards explainable unsupervised deep learning with applications to condition monitoring under covariate shift by Yong, Bang Xiang, Brintrup, Alexandra

“…, the Bayesian autoencoder (BAE). These formulations contrast the conventional post-hoc explanation methods for AEs, which incur additional modelling effort and implementations…”
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Accelerator tuning method using autoencoder and Bayesian optimization by Morita, Yasuyuki, Washio, Takashi, Nakashima, Yuta

“… In recent years, tuning methods based on machine learning have been extensively studied. Bayesian optimization (BO…”
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Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach by Siva Raja, P.M., rani, Antony Viswasa

“… This paper developed a brain tumor classification using a hybrid deep autoencoder with a Bayesian fuzzy clustering-based segmentation approach…”
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HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization by Dorier, Matthieu, Egele, Romain, Balaprakash, Prasanna, Koo, Jaehoon, Madireddy, Sandeep, Ramesh, Srinivasan, Malony, Allen D., Ross, Rob

“… To address this issue, we develop a novel variational-autoencoder-guided asynchronous Bayesian optimization method to tune HPC storage service parameters…”
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Variational Bayesian Autoencoder for Channel Compression and Feedback in Massive MIMO Systems by Zheng, Xuanyu, Bi, Yuanyuan, Guo, Huayan, Lau, Vincent

“…In this paper, we propose a Variational Bayesian Autoencoder (VBA)-based channel state information (CSI…”
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Designing thermal radiation metamaterials via a hybrid adversarial autoencoder and Bayesian optimization by Zhu, Dezhao, Guo, Jiang, Yu, Gang, Zhao, C Y, Wang, Hong, Ju, Shenghong

“… In this Letter, we develop a hybrid materials informatics approach which combines the adversarial autoencoder and Bayesian optimization to design narrowband thermal emitters at different target wavelengths…”
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Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches by Tehrani, Ali K. Z., Cloutier, Guy, Tang, An, Rosado-Mendez, Ivan M., Rivaz, Hassan

“…Quantitative ultrasound (QUS) analyzes the ultrasound (US) backscattered data to find the properties of scatterers that correlate with the tissue…”
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Combining autoencoder neural network and Bayesian inversion to estimate heterogeneous permeability distributions in enhanced geothermal reservoir: Model development and verification by Jiang, Zhenjiao, Zhang, Siyu, Turnadge, Chris, Xu, Tianfu

“…•Autoencoder neural network is developed for 3D parameter dimension reduction.•Neural network releases prior Gaussian assumption and shortens the burn-in period…”
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Publisher's Note: "Deep network fault diagnosis for imbalanced small-sized samples via a coupled adversarial autoencoder based on the Bayesian method" [Rev. Sci. Instrum. 95, 055104 (2024)] by Zhang, Xinliang, Wang, Yanqi, Zhou, Yitian, Jia, Lijie

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An adaptive mixture prior in Bayesian convolutional autoencoder for early detecting anomalous degradation behaviors in lithium-ion batteries by Chae, Sun Geu, Bae, Suk Joo

“… This paper proposes an unsupervised adaptive mixture distribution-based Bayesian convolutional autoencoder (AMDBCAE…”
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Predictive Body Awareness in Soft Robots: A Bayesian Variational Autoencoder Fusing Multimodal Sensory Data by Wang, Shuyu, Liu, Dongling, Fu, Changzeng, Yuan, Xiaoming, Shan, Peng, Leung, Victor C.M.

“… In this study, we leverage the free energy principle within a Bayesian probabilistic deep learning framework to merge visual, pressure, and flex sensing signals…”
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EXTENDING THE LEE–CARTER MODEL WITH VARIATIONAL AUTOENCODER: A FUSION OF NEURAL NETWORK AND BAYESIAN APPROACH by Miyata, Akihiro, Matsuyama, Naoki

“… autoencoder that performs the variational Bayesian estimation of a state…”
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Robust Multiple-Measurement Sparsity-Aware STAP with Bayesian Variational Autoencoder by Zhang, Chenxi, Zhao, Huiliang, Chen, Wenchao, Chen, Bo, Wang, Penghui, Jia, Changrui, Liu, Hongwei

“…Due to the shortage of independent and identically distributed (i.i.d.) training samples, space−time adaptive processing (STAP) often suffers remarkable…”
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