Výsledky vyhľadávania - Multi-Modal Variational Autoencoder*
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MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling
ISSN: 1053-8119, 1095-9572, 1095-9572Vydavateľské údaje: United States Elsevier Inc 01.03.2023Vydané 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
ISSN: 1433-7541, 1433-755XVydavateľské údaje: London Springer London 01.06.2025Vydané v Pattern analysis and applications : PAA (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
ISSN: 0956-540X, 1365-246XVydavateľské údaje: Oxford University Press 01.12.2023Vydané 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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Geometry-informed multimodal variational autoencoder for real-time prediction of properties for Ti–6Al–4V fabricated using PBF-LB
ISSN: 0956-5515, 1572-8145Vydavateľské údaje: 11.10.2025Vydané 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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Normative Modeling using Multimodal Variational Autoencoders to Identify Abnormal Brain Volume Deviations in Alzheimer's Disease
ISSN: 0277-786XVydavateľské údaje: United States 01.02.2023Vydané v Proceedings of SPIE, the international society for optical engineering (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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Anytime 3D Object Reconstruction Using Multi-Modal Variational Autoencoder
ISSN: 2377-3766, 2377-3766Vydavateľské údaje: Piscataway IEEE 01.04.2022Vydané 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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Bayesian mixture variational autoencoders for multi-modal learning
ISSN: 0885-6125, 1573-0565Vydavateľské údaje: New York Springer US 01.12.2022Vydané 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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Combined Generation of Electrocardiogram and Cardiac Anatomy Models Using Multi-Modal Variational Autoencoders
ISSN: 1945-8452Vydavateľské údaje: IEEE 28.03.2022Vydané v Proceedings (International Symposium on Biomedical Imaging) (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
ISSN: 2329-9266, 2329-9274Vydavateľské údaje: Piscataway Chinese Association of Automation (CAA) 01.09.2022Vydané 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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Multi-modal hybrid modeling strategy based on Gaussian Mixture Variational Autoencoder and spatial–temporal attention: Application to industrial process prediction
ISSN: 0169-7439Vydavateľské údaje: 15.01.2024Vydané v Chemometrics and intelligent laboratory systems (15.01.2024)Získať plný text
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Time-Lag Aware Multi-Modal Variational Autoencoder Using Baseball Videos And Tweets For Prediction Of Important Scenes
ISSN: 2381-8549Vydavateľské údaje: IEEE 01.01.2021Vydané v Proceedings - International Conference on Image Processing (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
ISSN: 0045-7825, 1879-2138Vydavateľské údaje: Elsevier B.V 01.09.2024Vydané v Computer methods in applied mechanics and engineering (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
ISSN: 2168-2194, 2168-2208, 2168-2208Vydavateľské údaje: United States IEEE 01.03.2022Vydané v IEEE journal of biomedical and health informatics (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
ISSN: 0952-1976, 1873-6769Vydavateľské údaje: Elsevier Ltd 01.06.2023Vydané v Engineering applications of artificial intelligence (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
ISSN: 1424-8220, 1424-8220Vydavateľské údaje: Switzerland MDPI AG 14.03.2021Vydané 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
ISSN: 2045-2322, 2045-2322Vydavateľské údaje: London Nature Publishing Group UK 24.11.2025Vydané 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
ISSN: 0924-669X, 1573-7497Vydavateľské údaje: New York Springer US 01.11.2023Vydané v Applied intelligence (Dordrecht, Netherlands) (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
ISSN: 2169-3536, 2169-3536Vydavateľské údaje: Piscataway IEEE 01.01.2025Vydané 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
ISSN: 2168-2194, 2168-2208, 2168-2208Vydavateľské údaje: United States IEEE 01.02.2022Vydané v IEEE journal of biomedical and health informatics (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
ISSN: 0893-6080, 1879-2782, 1879-2782Vydavateľské údaje: United States Elsevier Ltd 01.04.2024Vydané 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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