Výsledky vyhledávání - improved conditioning variational autoencoder

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    Self-supervised Variational Autoencoder for Unsupervised Object Counting from Very High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas Autor Gella, Getachew Workineh, Gangloff, Hugo, Wendt, Lorenz, Tiede, Dirk, Lang, Stefan

    ISSN: 0196-2892, 1558-0644
    Vydáno: New York IEEE 01.01.2024
    “… This constrains their utility in humanitarian emergency response. To overcome this problem, we have proposed an unsupervised dwelling counting from very high-resolution satellite imagery by combining a Variational Autoencoder(VAE…”
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    Chiller fault diagnosis based on improved variational autoencoder and co-training framework: A case study of insufficient samples Autor Lu, Cheng, Ma, Xiang, Yan, Ke

    ISSN: 2352-7102, 2352-7102
    Vydáno: Elsevier Ltd 01.07.2024
    Vydáno v Journal of Building Engineering (01.07.2024)
    “… This paper proposes a method based on an improved conditional variational autoencoder (MCVAE) and co-training (CT) ideology to address the issue of insufficient training samples…”
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    Development of a surrogate model to improve the efficiency of groundwater level fluctuation pattern-based hydrologic properties evaluation Autor Jeong, Jiho, Jeong, Jina

    ISSN: 0022-1694, 1879-2707
    Vydáno: Elsevier B.V 01.04.2023
    Vydáno v Journal of hydrology (Amsterdam) (01.04.2023)
    “…•The feature extraction was based on a conditional variational autoencoder.•The uncertainty due to different precipitation patterns was reduced…”
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    Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection Autor Xie, Qin, Zhang, Peng, Yu, Boseon, Choi, Jaesik

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydáno: United States IEEE 01.06.2022
    “…Abnormal behaviors in industrial systems may be early warnings on critical events that may cause severe damages to facilities and security. Thus, it is…”
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    Integration of Deep Learning‐Based Inversion and Upscaled Mass‐Transfer Model for DNAPL Mass‐Discharge Estimation and Uncertainty Assessment Autor Kang, Xueyuan, Kokkinaki, Amalia, Shi, Xiaoqing, Yoon, Hongkyu, Lee, Jonghyun, Kitanidis, Peter K., Wu, Jichun

    ISSN: 0043-1397, 1944-7973
    Vydáno: Washington John Wiley & Sons, Inc 01.10.2022
    Vydáno v Water resources research (01.10.2022)
    “…The challenges posed by high‐resolution characterization of dense nonaqueous phase liquid (DNAPL) source zone architecture (SZA) have motivated the development…”
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    Deep conditional generative model for personalization of 12-lead electrocardiograms and cardiovascular risk prediction Autor Sang, Yuling, Banerjee, Abhirup, Beetz, Marcel, Grau, Vicente

    ISSN: 2673-253X, 2673-253X
    Vydáno: Switzerland Frontiers Media S.A 16.04.2025
    Vydáno v Frontiers in digital health (16.04.2025)
    “… We propose a conditional Variational Autoencoder (cVAE) framework to generate realistic, subject-specific 12-lead ECGs…”
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    Investigation of F0 conditioning and Fully Convolutional Networks in Variational Autoencoder based Voice Conversion Autor Wen-Chin, Huang, Yi-Chiao, Wu, Chen-Chou, Lo, Tobing, Patrick Lumban, Hayashi, Tomoki, Kobayashi, Kazuhiro, Toda, Tomoki, Tsao, Yu, Wang, Hsin-Min

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 08.07.2019
    Vydáno v arXiv.org (08.07.2019)
    “…In this work, we investigate the effectiveness of two techniques for improving variational autoencoder (VAE…”
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    Hierarchical and Multi-Scale Variational Autoencoder for Diverse and Natural Non-Autoregressive Text-to-Speech Autor Jae-Sung Bae, Yang, Jinhyeok, Tae-Jun Bak, Young-Sun, Joo

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 15.08.2022
    Vydáno v arXiv.org (15.08.2022)
    “…This paper proposes a hierarchical and multi-scale variational autoencoder-based non-autoregressive text-to-speech model (HiMuV-TTS…”
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    Harnessing Generative Deep Learning for Enhanced Ensemble Data Assimilation Autor Foroumandi, Ehsan, Moradkhani, Hamid

    ISSN: 0043-1397, 1944-7973
    Vydáno: Washington John Wiley & Sons, Inc 01.07.2025
    Vydáno v Water resources research (01.07.2025)
    “…‐based autoencoders, and deep generative modeling to perform DA in a unified latent space and finally a resampling…”
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    Improved Variational Autoencoders for Text Modeling using Dilated Convolutions Autor Yang, Zichao, Hu, Zhiting, Salakhutdinov, Ruslan, Berg-Kirkpatrick, Taylor

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 18.06.2017
    Vydáno v arXiv.org (18.06.2017)
    “…Recent work on generative modeling of text has found that variational auto-encoders (VAE…”
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    Invariant Representations from Adversarially Censored Autoencoders Autor Wang, Ye, Koike-Akino, Toshiaki, Erdogmus, Deniz

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 21.05.2018
    Vydáno v arXiv.org (21.05.2018)
    “…We combine conditional variational autoencoders (VAE) with adversarial censoring in order to learn invariant representations that are disentangled from nuisance/sensitive variations…”
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    Enhanced Realism in Virtual Try-On Tasks Using Diffusion Methods Autor Kiattithapanayong, Saris, Phoomvuthisarn, Suronapee

    Vydáno: IEEE 28.03.2025
    “… Our approach integrates Vector Quantized Variational Autoencoders (VQ-VAEs) for precise feature matching within a diffusion U-Net architecture…”
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    Framing the Sequence: Genre-Aligned Photo Curation via Shot-Scale Embedding Autor Park, Youngsup, Lim, Yangmi, Kang, Dongwann

    ISSN: 2079-9292, 2079-9292
    Vydáno: Basel MDPI AG 01.09.2025
    Vydáno v Electronics (Basel) (01.09.2025)
    “…) a conditional variational autoencoder (cVAE) for embedding temporal shot rhythms conditioned on genre, and (3…”
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    Multimodal image synthesis based on disentanglement representations of anatomical and modality specific features, learned using uncooperative relativistic GAN Autor Reaungamornrat, Sureerat, Sari, Hasan, Catana, Ciprian, Kamen, Ali

    ISSN: 1361-8415, 1361-8423, 1361-8423
    Vydáno: Netherlands Elsevier B.V 01.08.2022
    Vydáno v Medical image analysis (01.08.2022)
    “… minimization of the objective function and sparsify gradients, which, in turn, could improve ill-conditioning and training stability…”
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    조건부 생성모델을 이용한 강수 패턴에 따른 지하수위 생성 및 이의 활용에 관한 연구 Autor 정지호(Jiho Jeong), 정진아(Jina Jeong), 이병선(Byung Sun Lee), 송성호(Sung-Ho Song)

    ISSN: 1225-7281, 2288-7962
    Vydáno: Korea Society Of Economic&Environmental Geology 28.02.2021
    Vydáno v 자원환경지질 (28.02.2021)
    “…). In their study, low-dimensional features of the annual groundwater level (GWL) fluctuation patterns extracted based on a Denoising autoencoder (DAE…”
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    Diffusion models for multivariate subsurface generation and efficient probabilistic inversion Autor Miele, Roberto, Linde, Niklas

    ISSN: 0098-3004
    Vydáno: Elsevier Ltd 01.02.2026
    Vydáno v Computers & geosciences (01.02.2026)
    “… We first demonstrate that diffusion models enhance multivariate modeling capabilities compared to variational autoencoders and generative adversarial networks…”
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    An innovative model integrating dual-channel graph attention network and multi-task learning for building energy consumption anomaly detection Autor Tian, Chongyi, Liu, Qiang, Tian, Changbin, Ma, Xin, Kong, Weizheng

    ISSN: 0360-1323
    Vydáno: Elsevier Ltd 01.01.2026
    Vydáno v Building and environment (01.01.2026)
    “…•Dual-channel GAT jointly models multivariate couplings and temporal dependencies.•Anomaly score based on dynamically weighted prediction and…”
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    Latent space conditioning for improved classification and anomaly detection Autor Norlander, Erik, Sopasakis, Alexandros

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 28.11.2019
    Vydáno v arXiv.org (28.11.2019)
    “…We propose a new type of variational autoencoder to perform improved pre-processing for clustering and anomaly detection on data with a given label…”
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    Generative Models for Improved Naturalness, Intelligibility, and Voicing of Whispered Speech Autor Wagner, Dominik, Bayerl, Sebastian P., Maruri, Hector A. Cordourier, Bocklet, Tobias

    Vydáno: IEEE 09.01.2023
    “… We incorporate the normal target speech into the training criterion of vector-quantized variational autoencoders (VQ-VAEs…”
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