Suchergebnisse - (beta OR bela)-convolutional variational autoencoder

A robust variational autoencoder using beta divergence von Akrami, Haleh, Joshi, Anand A., Li, Jian, Aydöre, Sergül, Leahy, Richard M.

“… ) are not present in the training data. Here we focus on variational autoencoders (VAEs). While the VAE is a popular framework for anomaly detection tasks, we observe …”
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An Unsupervised Approach to Wind Turbine Blade Icing Detection Based on Beta Variational Graph Attention Autoencoder von Wang, Lei, He, Yigang, Shao, Kaixuan, Xing, Zhikai, Zhou, Yazhong

“… To address these shortcomings, the current study proposes a Beta variational graph attention autoencoder (β-VGATAE) for blade ID. The β …”
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β-Variational autoencoders and transformers for reduced-order modelling of fluid flows von Solera-Rico, Alberto, Sanmiguel Vila, Carlos, Gómez-López, Miguel, Wang, Yuning, Almashjary, Abdulrahman, Dawson, Scott T. M., Vinuesa, Ricardo

“… Variational autoencoder architectures have the potential to develop reduced-order models for chaotic fluid flows …”
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β-Variational autoencoder as an entanglement classifier von Sá, Nahum, Roditi, Itzhak

“… We focus on using an architecture similar to the β-Variational Autoencoder (β-VAE) to discriminate if a quantum state is entangled or separable based on measurements …”
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Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic von Chow, Yuen Ler, Singh, Shantanu, Carpenter, Anne E., Way, Gregory P.

“… A variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space …”
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Spatial-Frequency-Scale Variational Autoencoder for Enhanced Flow Diagnostics of Schlieren Data von Yang, Ronghua, Wu, Hao, Yang, Rongfei, Wu, Xingshuang, Song, Yifan, Lü, Meiying, Wang, Mingrui

“… In this study, we propose a Spatial-Frequency-Scale variational autoencoder (SFS-VAE), a deep learning framework designed for the unsupervised feature decomposition of Schlieren sensor data …”
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Elucidating Protein Dynamics through the Optimal Annealing of Variational Autoencoders von Adhikari, Subinoy, Mondal, Jagannath

“… However, unraveling these dynamics remains a formidable challenge. An emerging approach has been to train the conformational ensemble via deep Variational autoencoders (VAEs …”
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A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data von Liu, Bin, Rosenhahn, Bodo, Illig, Thomas, DeLuca, David S.

“… that drive transcriptome signals. We investigate whether simple, variational autoencoder (VAE), and beta-weighted VAE are capable of learning reduced representations of transcriptomes that retain critical biological information …”
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Disentangled representational learning for anomaly detection in single-lead electrocardiogram signals using variational autoencoder von Kapsecker, Maximilian, Möller, Matthias C., Jonas, Stephan M.

“… A beta total correlation variational autoencoder was optimized on four of these datasets for 68 systematic parameterization variants …”
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An Overview of Variational Autoencoders for Source Separation, Finance, and Bio-Signal Applications von Singh, Aman, Ogunfunmi, Tokunbo

“… Variational Autoencoders (VAEs) can be regarded as enhanced Autoencoders where a Bayesian approach is used to learn the probability distribution of the input …”
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A dimensionality reduction algorithm for mapping tokamak operational regimes using a variational autoencoder (VAE) neural network von Wei, Y., Levesque, J.P., Hansen, C.J., Mauel, M.E., Navratil, G.A.

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Mathematical Modeling of Aβ-42 Dimerization Dynamics: Integrating Physics-Based Simulations, Graph-Based Variational Autoencoder-Driven Neural Relational Inference, and Chaos Theory von Sayyah, Ehsan, Kurul, Emel, Tunç, Hüseyin, Durdağı, Serdar

“… Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the pathological aggregation of amyloid-beta (Aβ …”
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FVAE: a regularized variational autoencoder using the Fisher criterion von Lai, Jie, Wang, Xiaodan, Xiang, Qian, Li, Rui, Song, Yafei

“… As a deep generative model, the variational autoencoder (VAE) is widely applied to solve problems of insufficient samples and imbalanced labels …”
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Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder von Cao, Shichen, Li, Jingjing, Nelson, Kenric P., Kon, Mark A.

“… We present a coupled variational autoencoder (VAE) method, which improves the accuracy and robustness of the model representation of handwritten numeral images …”
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Quality-related nonlinear process monitoring of power plant by a novel hybrid model based on variational autoencoder von Wang, Peng, Ren, Shaojun, Wang, Yan, Zhu, Baoyu, Fan, Wei, Si, Fengqi

“… In this paper, a novel hybrid model called information bottleneck-based variational autoencoder with supervised regression (IBVAE-SR …”
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Research on multi-heat source arrangement optimization based on equivalent heat source method and reconstructed variational autoencoder von Yang, Yide, Gong, Mali, Ma, Jianshe

“… The variational autoencoder (VAE) architecture has significant advantages in predictive image generation …”
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Source Separation in Joint Communication and Radar Systems Based on Unsupervised Variational Autoencoder von Alaghbari, Khaled A., Lim, Heng Siong, Jin, Benzhou, Shen, Yutong

“… ) systems to achieve the required performance, especially at a low signal-to-noise ratio (SNR). In this paper, we propose the use of a generative model, such as the unsupervised variational autoencoder …”
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Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders von Kieu, Tung, Yang, Bin, Guo, Chenjuan, Cirstea, Razvan-Gabriel, Zhao, Yan, Song, Yale, Jensen, Christian S.

“… We propose variational quasi-recurrent autoencoders (VQRAEs) to enable robust and efficient anomaly detection in time series in unsupervised settings …”
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A Two-Stage Deep Representation Learning-Based Speech Enhancement Method Using Variational Autoencoder and Adversarial Training von Xiang, Yang, Hojvang, Jesper Lisby, Rasmussen, Morten Hojfeldt, Christensen, Mads Graesboll

“… Specifically, we use the <inline-formula><tex-math notation="LaTeX">\beta</tex-math></inline-formula>-variational autoencoder …”
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Unsupervised machinery prognostics approach based on wavelet packet decomposition and variational autoencoder von Franco de Godói, Leonardo, de Oliveira Nóbrega, Eurípedes Guilherme

“… This paper proposes a novel method for generating a degradation indicator to estimate the remaining useful life of rotating machinery critical components, based on a beta variational autoencoder …”
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