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    Optimal Dimensionality Reduction using Conditional Variational AutoEncoder by Sana Boussam, Mathieu Carbone, Benoît Gérard, Guénaël Renault, Gabriel Zaid

    Published 2025-06-01
    “…This model is based on conditional variational autoencoder and converges towards the optimal statistical model i.e. it performs an optimal attack. …”
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    Comparing factor mixture modeling and conditional Gaussian mixture variational autoencoders for cognitive profile clustering by Matteo Orsoni, Sara Giovagnoli, Sara Garofalo, Noemi Mazzoni, Matilde Spinoso, Mariagrazia Benassi

    Published 2025-05-01
    “…While traditional methods like factor mixture modeling (FMM) have proven robust for identifying latent cognitive structures, recent advancements in deep learning may offer the potential to capture more intricate and complex cognitive patterns.MethodsThis study compares FMM (specifically, FMM-1 and FMM-2 models using age as a covariate) with a Conditional Gaussian Mixture Variational Autoencoder (CGMVAE). …”
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    Style-VT: Style Conditioned Chord Generation by Variational Transformer With Chord Substitution by Kyowon Song, Dongyoung Seo, Junsu Na, Heecheol Yang

    Published 2025-01-01
    “…In this work, we present Style-VT, a style-conditioned chord generation model that combines the Transformer architecture with a variational autoencoder. …”
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    Convolutional Variational Autoencoder for Anomaly Detection in On-Load Tap Changers by Fataneh Dabaghi-Zarandi, Hassan Ezzaidi, Michel Gauvin, Patrick Picher, Issouf Fofana, Vahid Behjat

    Published 2025-01-01
    “…To detect anomalies in OLTCs and analyze the generated vibration signals, a convolutional variational autoencoder (CVAE) is utilized, trained individually for each transformer family. …”
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    Discrete variational autoencoders for synthetic nighttime visible satellite imagery by Mickell D. Als, David Tomarov, Steve Easterbrook

    Published 2025-01-01
    “…To address this limitation, we present a discrete variational autoencoder (VQVAE) method for translating infrared satellite imagery to VIS. …”
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    ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking by Chih-Yu Hsu, Chih-Yin Chang, Yin-Chi Chen, Jasper Wu, Shuo-Tsung Chen

    Published 2025-04-01
    “…A Variational Autoencoder (VAE) framework is employed to generate the watermarked ECG signals, addressing critical concerns in the digital era, such as data security, authenticity, and copyright protection. …”
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    Marked point process variational autoencoder with applications to unsorted spiking activities. by Ryohei Shibue, Tomoharu Iwata

    Published 2024-12-01
    “…To address this limitation, we propose a new joint mark intensity model based on a variational autoencoder, capable of representing the dependency structure of unsorted spikes on observed covariates or hidden states in a data-driven manner. …”
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    Quantum Variational Autoencoder Based on Weak Measurements With Fuzzy Filtering of Input Data by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodsinskyi

    Published 2025-03-01
    “…The article first proposes a quantum variational autoencoder (QVA) based on weak measurements, which expands the space of possible solutions due to quantum effects – qubit entanglement, superposition of states and information teleportation. …”
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    Variational Autoencoder Based Anomaly Detection in Large-Scale Energy Storage Power Stations by Tuo Ji, Pinghu Xu, Dongliang Guo, Lei Sun, Kangji Ma, Yanan Wang, Xuebing Han

    Published 2025-05-01
    “…This study employs an unsupervised deep learning model based on variational autoencoders (VAEs) to perform anomaly detection on real operational data. …”
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    Article
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