Výsledky vyhľadávania - beta-convolutional variational autoencoder

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  1. 1

    History matching of a three dimensional channelized reservoir using a beta-convolutional variational autoencoder and ensemble smoother with multiple data assimilation Autor Ahn, Youngbin, Choe, Jonggeun, Min, Baehyun

    ISSN: 0952-1976
    Vydavateľské údaje: Elsevier Ltd 01.11.2025
    “… The study's scheme was divided into three stages. First, a beta-convolutional variational autoencoder network was trained using rock facies of reservoir models…”
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  2. 2

    Fault Diagnosis of Machines Using Deep Convolutional Beta-Variational Autoencoder Autor Dewangan, Gaurav, Maurya, Seetaram

    ISSN: 2691-4581, 2691-4581
    Vydavateľské údaje: IEEE 01.04.2022
    “… In this article, a novel intelligent fault diagnosis scheme based on deep convolutional variable-beta variational autoencoder (VAE…”
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  3. 3

    Investigating Beta-Variational Convolutional Autoencoders for the Unsupervised Classification of Chest Pneumonia Autor Akila, Serag Mohamed, Imanov, Elbrus, Almezhghwi, Khaled

    ISSN: 2075-4418, 2075-4418
    Vydavateľské údaje: Switzerland MDPI AG 28.06.2023
    Vydané v Diagnostics (Basel) (28.06.2023)
    “…The world’s population is increasing and so is the challenge on existing healthcare infrastructure to cope with the growing demand in medical diagnosis and…”
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  4. 4

    A deep-learning search for technosignatures from 820 nearby stars Autor Ma, Peter Xiangyuan, Ng, Cherry, Rizk, Leandro, Croft, Steve, Siemion, Andrew P. V, Brzycki, Bryan, Czech, Daniel, Drew, Jamie, Gajjar, Vishal, Hoang, John, Isaacson, Howard, Lebofsky, Matt, MacMahon, David H. E, de Pater, Imke, Price, Danny C, Sheikh, Sofia Z, Worden, S. Pete

    ISSN: 2397-3366
    Vydavateľské údaje: London Nature Publishing Group 01.04.2023
    Vydané v Nature astronomy (01.04.2023)
    “… We implement a novel β-convolutional variational autoencoder to identify technosignature candidates in a semi-unsupervised manner while keeping…”
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  5. 5

    A deep-learning search for technosignatures of 820 nearby stars Autor Xiangyuan, Peter, Ng, Cherry, Rizk, Leandro, Croft, Steve, Siemion, Andrew P V, Brzycki, Bryan, Czech, Daniel, Drew, Jamie, Gajjar, Vishal, Hoang, John, Isaacson, Howard, Lebofsky, Matt, MacMahon, David, de Pater, Imke, Price, Danny C, Sheikh, Sofia Z, Worden, S Pete

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 30.01.2023
    Vydané v arXiv.org (30.01.2023)
    “… We implement a novel beta-Convolutional Variational Autoencoder to identify…”
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  6. 6

    Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Autor Eivazi, Hamidreza, Le Clainche, Soledad, Hoyas, Sergio, Vinuesa, Ricardo

    ISSN: 0957-4174, 1873-6793, 1873-6793
    Vydavateľské údaje: New York Elsevier Ltd 15.09.2022
    Vydané v Expert systems with applications (15.09.2022)
    “…-order modeling and flow control. Our approach is based on β-variational autoencoders (β-VAEs) and convolutional neural networks…”
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  7. 7

    An efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks Autor Gergs, Tobias, Borislavov, Borislav, Trieschmann, Jan

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 06.09.2021
    Vydané v arXiv.org (06.09.2021)
    “…Simulations of thin film sputter deposition require the separation of the plasma and material transport in the gas-phase from the growth/sputtering processes…”
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  8. 8

    Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Autor Eivazi, Hamidreza, Soledad Le Clainche, Hoyas, Sergio, Vinuesa, Ricardo

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 03.09.2021
    Vydané v arXiv.org (03.09.2021)
    “…, reduced-order modeling, and flow control. Our approach is based on \(\beta\)-variational autoencoders (\(\beta\)-VAEs…”
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  9. 9

    Graph-Convolutional-Beta-VAE for synthetic abdominal aortic aneurysm generation Autor Fabbri, Francesco, Scarpolini, Martino Andrea, Iollo, Angelo, Viola, Francesco, Tudisco, Francesco

    ISSN: 1741-0444
    Vydavateľské údaje: United States 04.12.2025
    “… This study presents a Graph Convolutional Neural Network combined with a Beta-Variational Autoencoder (GCN-β-VAE…”
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  10. 10

    AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders Autor Glushkovsky, Alex

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 14.12.2021
    Vydané v arXiv.org (14.12.2021)
    “… Latent space representation has been performed using a convolutional beta variational autoencoder (beta-VAE…”
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  11. 11

    Deciphering the Coevolutionary Dynamics of L2 β-Lactamases via Deep Learning Autor Zhu, Yu, Gu, Jing, Zhao, Zhuoran, Chan, A W Edith, Mojica, Maria F, Hujer, Andrea M, Bonomo, Robert A, Haider, Shozeb

    ISSN: 1549-960X, 1549-960X
    Vydavateľské údaje: United States 13.05.2024
    “… (convolutional variational autoencoders and BindSiteS-CNN) explored conformational changes and correlations within the L2 β…”
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  12. 12

    Evolutionary Dynamics and Functional Differences in Clinically Relevant Pen β-Lactamases from Burkholderia spp Autor Gu, Jing, Agarwal, Pratul K, Bonomo, Robert A, Haider, Shozeb

    ISSN: 1549-960X, 1549-960X
    Vydavateľské údaje: United States 26.05.2025
    “…), convolutional variational autoencoder-based deep learning (CVAE) and the BindSiteS-CNN model. In spite of sharing the same catalytic mechanisms, these enzymes exhibit…”
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  13. 13

    A 3D lung lesion variational autoencoder Autor Li, Yiheng, Sadée, Christoph Y., Carrillo-Perez, Francisco, Selby, Heather M., Thieme, Alexander H., Gevaert, Olivier

    ISSN: 2667-2375, 2667-2375
    Vydavateľské údaje: United States Elsevier Inc 26.02.2024
    Vydané v Cell reports methods (26.02.2024)
    “…In this study, we develop a 3D beta variational autoencoder (beta-VAE) to advance lung cancer imaging analysis, countering the constraints of conventional radiomics methods…”
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