Výsledky vyhľadávania - (conditional OR conditioning) variational autoencoder*

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    Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy Autor Gabbard, Hunter, Messenger, Chris, Heng, Ik Siong, Tonolini, Francesco, Murray-Smith, Roderick

    ISSN: 1745-2473, 1745-2481
    Vydavateľské údaje: London Nature Publishing Group UK 01.01.2022
    Vydané v Nature physics (01.01.2022)
    “… min on a limited range of key source parameters. Here, we show that a conditional variational autoencoder pretrained on binary black hole signals can return Bayesian…”
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    Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network Autor Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Yang, Yixian

    ISSN: 1424-8220, 1424-8220
    Vydavateľské údaje: Switzerland MDPI AG 02.06.2019
    Vydané v Sensors (Basel, Switzerland) (02.06.2019)
    “… We propose a novel intrusion detection model that combines an improved conditional variational AutoEncoder (ICVAE…”
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    Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT Autor Lopez-Martin, Manuel, Carro, Belen, Sanchez-Esguevillas, Antonio, Lloret, Jaime

    ISSN: 1424-8220, 1424-8220
    Vydavateľské údaje: Switzerland MDPI AG 26.08.2017
    Vydané v Sensors (Basel, Switzerland) (26.08.2017)
    “…The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current…”
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    Molecular generative model based on conditional variational autoencoder for de novo molecular design Autor Lim, Jaechang, Ryu, Seongok, Kim, Jin Woo, Kim, Woo Youn

    ISSN: 1758-2946, 1758-2946
    Vydavateľské údaje: Cham Springer International Publishing 11.07.2018
    Vydané v Journal of cheminformatics (11.07.2018)
    “…We propose a molecular generative model based on the conditional variational autoencoder for de novo molecular design…”
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    Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Conditional Variational Autoencoders-Particle Filter Autor Jiao, Ruihua, Peng, Kaixiang, Dong, Jie

    ISSN: 0018-9456, 1557-9662
    Vydavateľské údaje: New York IEEE 01.11.2020
    “… In this article, a novel PF framework based on conditional variational autoencoder (CVAE) and a reweighting strategy is proposed to predict the RUL of batteries…”
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    Data-driven design exploration method using conditional variational autoencoder for airfoil design Autor Yonekura, Kazuo, Suzuki, Katsuyuki

    ISSN: 1615-147X, 1615-1488
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2021
    “… In the present work, we achieve this goal using a conditional variational autoencoder (CVAE). The method enables us to analyze the relationship between aerodynamic performance and the shape of aerodynamic parts, and to explore new designs for the parts…”
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    UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders Autor Zhang, Jing, Fan, Deng-Ping, Dai, Yuchao, Anwar, Saeed, Saleh, Fatemeh Sadat, Zhang, Tong, Barnes, Nick

    ISSN: 1063-6919
    Vydavateľské údaje: IEEE 01.01.2020
    “… Inspired by the saliency data labeling process, we propose probabilistic RGB-D saliency detection network via conditional variational autoencoders to model human annotation uncertainty and generate…”
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    MGCVAE: Multi-Objective Inverse Design via Molecular Graph Conditional Variational Autoencoder Autor Lee, Myeonghun, Min, Kyoungmin

    ISSN: 1549-960X, 1549-960X
    Vydavateľské údaje: United States 27.06.2022
    “… The performance of the molecular graph conditional variational autoencoder (MGCVAE) for generating molecules with specific desired properties was investigated by comparing it to a molecular graph variational autoencoder (MGVAE…”
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    Robust Haze and Thin Cloud Removal via Conditional Variational Autoencoders Autor Ding, Haidong, Xie, Fengying, Qiu, Linwei, Zhang, Xiaozhe, Shi, Zhenwei

    ISSN: 0196-2892, 1558-0644
    Vydavateľské údaje: New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
    “… In this article, we present a novel algorithm for haze and thin cloud removal using conditional variational autoencoders (CVAEs…”
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    Masked conditional variational autoencoders for chromosome straightening Autor Li, Jingxiong, Zheng, Sunyi, Shui, Zhongyi, Zhang, Shichuan, Yang, Linyi, Sun, Yuxuan, Zhang, Yunlong, Li, Honglin, Ye, Yuanxin, Van Ooijen, Peter M.A., Li, Kang, Yang, Lin

    ISSN: 0278-0062, 1558-254X, 1558-254X
    Vydavateľské údaje: United States IEEE 01.01.2024
    Vydané v IEEE transactions on medical imaging (01.01.2024)
    “… To address this issue, we propose a framework for chromosome straightening, which comprises a preliminary processing algorithm and a generative model called masked conditional variational autoencoders (MC-VAE…”
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    KilonovaNet: Surrogate models of kilonova spectra with conditional variational autoencoders Autor Lukošiute, K, Raaijmakers, G, Doctor, Z, Soares-Santos, M, Nord, B

    ISSN: 0035-8711, 1365-2966
    Vydavateľské údaje: United Kingdom Oxford University Press 01.09.2022
    “… In this work, we present kilonovanet, an implementation of conditional variational autoencoders (cVAEs…”
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    Generating multivariate load states using a conditional variational autoencoder Autor Wang, Chenguang, Sharifnia, Ensieh, Gao, Zhi, Tindemans, Simon H., Palensky, Peter

    ISSN: 0378-7796, 1873-2046
    Vydavateľské údaje: Elsevier B.V 01.12.2022
    Vydané v Electric power systems research (01.12.2022)
    “… In this paper, a multivariate load state generating model on the basis of a conditional variational autoencoder (CVAE…”
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    Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders Autor Li, Jing, Kang, Di, Pei, Wenjie, Zhe, Xuefei, Zhang, Ying, He, Zhenyu, Bao, Linchao

    ISSN: 2380-7504
    Vydavateľské údaje: IEEE 01.10.2021
    “… In order to over-come this problem, we propose a novel conditional variational autoencoder (VAE…”
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    Power Plant Model Parameter Calibration Using Conditional Variational Autoencoder Autor Khazeiynasab, Seyyed Rashid, Zhao, Junbo, Batarseh, Issa, Tan, Bendong

    ISSN: 0885-8950, 1558-0679
    Vydavateľské údaje: New York IEEE 01.03.2022
    Vydané v IEEE transactions on power systems (01.03.2022)
    “… Then, synchrophasor measurement-based conditional variational autoencoder is developed to estimate the parameters' posterior distributions even in the presence of a high-dimensional case…”
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    Generalized zero-shot domain adaptation via coupled conditional variational autoencoders Autor Wang, Qian, Breckon, Toby P.

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Vydavateľské údaje: United States Elsevier Ltd 01.06.2023
    Vydané v Neural networks (01.06.2023)
    “…Domain adaptation aims to exploit useful information from the source domain where annotated training data are easier to obtain to address a learning problem in…”
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    Toward Effective Intrusion Detection Using Log-Cosh Conditional Variational Autoencoder Autor Xu, Xing, Li, Jie, Yang, Yang, Shen, Fumin

    ISSN: 2327-4662, 2327-4662
    Vydavateľské údaje: Piscataway IEEE 15.04.2021
    Vydané v IEEE internet of things journal (15.04.2021)
    “… To tackle this problem, in this article, we propose a novel deep learning-based intrusion detection method named log-cosh conditional variational autoencoder (LCVAE…”
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    Arbitrary conditional inference in variational autoencoders via fast prior network training Autor Wu, Ga, Domke, Justin, Sanner, Scott

    ISSN: 0885-6125, 1573-0565
    Vydavateľské údaje: New York Springer US 01.07.2022
    Vydané v Machine learning (01.07.2022)
    “…Variational Autoencoders (VAEs) are a popular generative model, but one in which conditional inference can be challenging…”
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    Learning the health index of complex systems using dynamic conditional variational autoencoders Autor Wei, Yupeng, Wu, Dazhong, Terpenny, Janis

    ISSN: 0951-8320, 1879-0836
    Vydavateľské údaje: Barking Elsevier Ltd 01.12.2021
    “…Recent advances in sensing technologies have enabled engineers to collect big data to predict the remaining useful life (RUL) of complex systems. Current…”
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