Výsledky vyhľadávania - Multi-Modal Variational Autoencoder*

  1. 1

    MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling Autor Martí-Juan, Gerard, Lorenzi, Marco, Piella, Gemma

    ISSN: 1053-8119, 1095-9572, 1095-9572
    Vydavateľské údaje: United States Elsevier Inc 01.03.2023
    Vydané v NeuroImage (Orlando, Fla.) (01.03.2023)
    “…•A multi-channel model based on recurrent variational autoencoders was proposed to capture spatial and temporal evolution of AD using multimodal data…”
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    Dmvae: a dual-stream multi-modal variational autoencoder for multi-task fake news detection Autor Guo, Ying, Hu, Shuting, Li, Yao, Di, Chong, Liu, Jie

    ISSN: 1433-7541, 1433-755X
    Vydavateľské údaje: London Springer London 01.06.2025
    “…The proliferation of fake news on social media platforms, facilitated by the development of the Internet, has become a pressing social issue, intensifying the urgency of detecting its diverse multi-modal forms…”
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    Multimodal variational autoencoder for inverse problems in geophysics: application to a 1-D magnetotelluric problem Autor Rodriguez, Oscar, Taylor, Jamie M, Pardo, David

    ISSN: 0956-540X, 1365-246X
    Vydavateľské údaje: Oxford University Press 01.12.2023
    Vydané v Geophysical journal international (01.12.2023)
    “… However, most geophysical applications exhibit more than one plausible solution. Here, we propose a multimodal variational autoencoder model that employs a mixture…”
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  4. 4

    Geometry-informed multimodal variational autoencoder for real-time prediction of properties for Ti–6Al–4V fabricated using PBF-LB Autor Luo, Qixiang, Huang, Nancy, Bartles, Dean L., Beese, Allison M.

    ISSN: 0956-5515, 1572-8145
    Vydavateľské údaje: 11.10.2025
    Vydané v Journal of intelligent manufacturing (11.10.2025)
    “…A geometry-informed multimodal variational autoencoder linear hybrid model (GMVAE) was developed to use in situ processing signals along with geometry information from laser scanning patterns to predict the mechanical properties of Ti-6Al-4…”
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  5. 5

    Normative Modeling using Multimodal Variational Autoencoders to Identify Abnormal Brain Volume Deviations in Alzheimer's Disease Autor Kumar, Sayantan, Payne, Philip R O, Sotiras, Aristeidis

    ISSN: 0277-786X
    Vydavateľské údaje: United States 01.02.2023
    “… To address this limitation, we propose a multi-modal variational autoencoder (mmVAE) based normative modelling framework that can capture the joint distribution between different modalities to identify…”
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  6. 6

    Anytime 3D Object Reconstruction Using Multi-Modal Variational Autoencoder Autor Yu, Hyeonwoo, Oh, Jean

    ISSN: 2377-3766, 2377-3766
    Vydavateľské údaje: Piscataway IEEE 01.04.2022
    Vydané v IEEE robotics and automation letters (01.04.2022)
    “… In a harsh remote collaboration setting, data compression techniques such as autoencoder can be utilized to obtain and transmit the data in terms of latent variables in a compact form…”
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  7. 7

    Bayesian mixture variational autoencoders for multi-modal learning Autor Liao, Keng-Te, Huang, Bo-Wei, Yang, Chih-Chun, Lin, Shou-De

    ISSN: 0885-6125, 1573-0565
    Vydavateľské údaje: New York Springer US 01.12.2022
    Vydané v Machine learning (01.12.2022)
    “…This paper provides an in-depth analysis on how to effectively acquire and generalize cross-modal knowledge for multi-modal learning. Mixture-of-Expert (MoE…”
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  8. 8

    Combined Generation of Electrocardiogram and Cardiac Anatomy Models Using Multi-Modal Variational Autoencoders Autor Beetz, Marcel, Banerjee, Abhirup, Sang, Yuling, Grau, Vicente

    ISSN: 1945-8452
    Vydavateľské údaje: IEEE 28.03.2022
    “… In this work, we propose a novel multi-modal variational autoencoder (VAE) capable of processing combined physiology and bitemporal anatomy information in the form of electrocardiograms (ECG…”
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    Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition Autor Wang, Yixin, Qiu, Shuang, Li, Dan, Du, Changde, Lu, Bao-Liang, He, Huiguang

    ISSN: 2329-9266, 2329-9274
    Vydavateľské údaje: Piscataway Chinese Association of Automation (CAA) 01.09.2022
    Vydané v IEEE/CAA journal of automatica sinica (01.09.2022)
    “… To solve this problem, we propose a multi-modal domain adaptive variational autoencoder (MMDA-VAE) method, which learns shared cross-domain latent representations of the multi-modal data…”
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    Time-Lag Aware Multi-Modal Variational Autoencoder Using Baseball Videos And Tweets For Prediction Of Important Scenes Autor Hirasawa, Kaito, Maeda, Keisuke, Ogawa, Takahiro, Haseyama, Miki

    ISSN: 2381-8549
    Vydavateľské údaje: IEEE 01.01.2021
    “…A novel method based on time-lag aware multi-modal variational autoencoder for prediction of important scenes (TI-MVAE-PIS…”
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    Bayesian structural model updating with multimodal variational autoencoder Autor Itoi, Tatsuya, Amishiki, Kazuho, Lee, Sangwon, Yaoyama, Taro

    ISSN: 0045-7825, 1879-2138
    Vydavateľské údaje: Elsevier B.V 01.09.2024
    “… The proposed method utilizes the surrogate unimodal encoders of a multimodal variational autoencoder (VAE…”
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    Explainable Dynamic Multimodal Variational Autoencoder for the Prediction of Patients With Suspected Central Precocious Puberty Autor Xu, Yiming, Liu, Xiaohong, Pan, Liyan, Mao, Xiaojian, Liang, Huiying, Wang, Guangyu, Chen, Ting

    ISSN: 2168-2194, 2168-2208, 2168-2208
    Vydavateľské údaje: United States IEEE 01.03.2022
    “…), and pelvic ultrasonography and left-hand radiography reports. The challenges are in integrating these multimodal features into a comprehensive deep learning model…”
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    One-class learning for fake news detection through multimodal variational autoencoders Autor Gôlo, Marcos Paulo Silva, de Souza, Mariana Caravanti, Rossi, Rafael Geraldeli, Rezende, Solange Oliveira, Nogueira, Bruno Magalhães, Marcacini, Ricardo Marcondes

    ISSN: 0952-1976, 1873-6769
    Vydavateľské údaje: Elsevier Ltd 01.06.2023
    “…Machine learning methods to detect fake news typically use textual features and Binary or Multi-class classification. However, accurately labeling a large news…”
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    Detection of Important Scenes in Baseball Videos via a Time-Lag-Aware Multimodal Variational Autoencoder Autor Hirasawa, Kaito, Maeda, Keisuke, Ogawa, Takahiro, Haseyama, Miki

    ISSN: 1424-8220, 1424-8220
    Vydavateľské údaje: Switzerland MDPI AG 14.03.2021
    Vydané v Sensors (Basel, Switzerland) (14.03.2021)
    “…A new method for the detection of important scenes in baseball videos via a time-lag-aware multimodal variational autoencoder (Tl-MVAE…”
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    Personalized design aesthetic preference modeling: a variational autoencoder and meta-learning approach for multi-modal feature representation and transfer optimization Autor Chen, Chengliang, Gong, Zhiqun

    ISSN: 2045-2322, 2045-2322
    Vydavateľské údaje: London Nature Publishing Group UK 24.11.2025
    Vydané v Scientific reports (24.11.2025)
    “…This research presents a comprehensive framework for personalized design aesthetic preference modeling that integrates variational autoencoders (VAE…”
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    iMVAN: integrative multimodal variational autoencoder and network fusion for biomarker identification and cancer subtype classification Autor Dhillon, Arwinder, Singh, Ashima, Bhalla, Vinod Kumar

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: New York Springer US 01.11.2023
    “…) for biomarker identification and cancer subtype classification. In this research, iMVAN, an integrated Multimodal Variational Autoencoder and Network fusion, is presented for biomarker discovery and classification of cancer subtypes…”
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    Improving news recommendation accuracy through multimodal variational autoencoder and adversarial training Autor Tang, Pei, Zhu, Shuo, Alatas, Bilal

    ISSN: 2169-3536, 2169-3536
    Vydavateľské údaje: Piscataway IEEE 01.01.2025
    Vydané v IEEE access (01.01.2025)
    “… A Multimodal Variational Autoencoder (MVAVE) is constructed based on the multi-head self-attention mechanism, incorporating noise injection for denoising to mitigate the impact of data noise on recommendation performance…”
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    Multimodal Disentangled Variational Autoencoder With Game Theoretic Interpretability for Glioma Grading Autor Cheng, Jianhong, Gao, Min, Liu, Jin, Yue, Hailin, Kuang, Hulin, Liu, Jun, Wang, Jianxin

    ISSN: 2168-2194, 2168-2208, 2168-2208
    Vydavateľské údaje: United States IEEE 01.02.2022
    “… In this study, we propose a deep neural network model termed as multimodal disentangled variational autoencoder (MMD-VAE…”
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    A multimodal dynamical variational autoencoder for audiovisual speech representation learning Autor Sadok, Samir, Leglaive, Simon, Girin, Laurent, Alameda-Pineda, Xavier, Séguier, Renaud

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Vydavateľské údaje: United States Elsevier Ltd 01.04.2024
    Vydané v Neural networks (01.04.2024)
    “… In particular, the variational autoencoder (VAE) which is equipped with both a generative and an inference model allows for the analysis, transformation, and generation of various types of data…”
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