Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders by Martin Gregurić, Filip Vrbanić, Edouard Ivanjko

Subjects: “…variational autoencoders…”
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Anomaly detection algorithm based on Gaussian mixture variational auto encoder network by Huahua CHEN, Zhe CHEN, Chunsheng GUO, Na YING, Xueyi YE, Jianwu ZHANG

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A Variational Multi-Scale Error Compensation Network for Single-Pixel Imaging by Jian Lin, Qiurong Yan, Quan Zou, Shida Sun, Zhen Wei, Hua Du

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Semi-supervised emotion-driven music generation model based on category-dispersed Gaussian Mixture Variational Autoencoders by Zihao Ning, Xiao Han, Jie Pan

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Efficient Prediction of Shallow-Water Acoustic Transmission Loss Using a Hybrid Variational Autoencoder–Flow Framework by Bolin Su, Haozhong Wang, Xingyu Zhu, Penghua Song, Xiaolei Li

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An enhanced deep learning‐based phishing detection mechanism to effectively identify malicious URLs using variational autoencoders by Manoj Kumar Prabakaran, Parvathy Meenakshi Sundaram, Abinaya Devi Chandrasekar

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Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment by Sikkandar Mohamed Yacin, Sabarunisha Begum S., Alassaf Ahmad, AlMohimeed Ibrahim, Alhussaini Khalid, Aleid Adham, Alhaidar Abdulrahman Khalid

“…This study introduces an innovative method for minimizing artifacts in electroencephalography (EEG) signals by integrating brainstorm optimization (BSO) with a variational autoencoder generative adversarial network (VAE-GAN), resulting in the BrOpt_VAGAN model. …”
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Paths Optimization by Jointing Link Management and Channel Estimation Using Variational Autoencoder With Attention for IRS-MIMO Systems by Meng-Hsun Wu, Hong-Yunn Chen, Ta-Wei Yang, Chih-Chuan Hsu, Chih-Wei Huang, Cheng-Fu Chou

“…Incorporating LM increased the sum rate and reduced MSE by approximately 9%. Variational autoencoders (VAE) outperformed traditional autoencoders in the spatial domain, as confirmed by heatmap analysis. …”
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Method for Determining Igneous Rock Mineral Content Using Element Logging Data Based on Variational AutoEncoder by JIA Ruilong, PAN Baozhi, WANG Qinghui, LI Yan, GUAN Yao, WANG Xinru

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Semi-supervised emotion-driven music generation model based on category-dispersed Gaussian Mixture Variational Autoencoders. by Zihao Ning, Xiao Han, Jie Pan

“…Building on this, a semi-supervised model is developed, leveraging a category-dispersed Gaussian mixture variational autoencoder to infer emotions from the latent representations of rhythm and tonal features. …”
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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

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Real-time Light Curve Classification Framework for the Wide Field Survey Telescope Using Modified Semisupervised Variational Autoencoder by Yongling Tang, Lulu Fan, Zhen Wan, Yating Liu, Yan Lu

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Prediction of post-irradiation swelling rate of 316L stainless steel based on Variational Autoencoders and interpretable machine learning by Chengcheng Liu, Hang Su

“…To address this issue, the study employed Variational Autoencoders (VAEs) for data augmentation, generating an additional 400 synthetic data points to expand the original dataset. …”
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Variational quantum classifier-based early identification and classification of chronic kidney disease using sparse autoencoder and LASSO shrinkage by P. Parthasarathi, Haya Mesfer Alshahrani, K. Venkatachalam, Jaehyuk Cho

“…In the second phase, data augmentation uses sparse autoencoders to balance the data for smaller classes. …”
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Detecting Emerging DGA Malware in Federated Environments via Variational Autoencoder-Based Clustering and Resource-Aware Client Selection by Ma Viet Duc, Pham Minh Dang, Tran Thu Phuong, Truong Duc Truong, Vu Hai, Nguyen Huu Thanh

“…To address this, we present FedSAGE, a security-aware federated intrusion detection framework that combines Variational Autoencoder (VAE)-based latent representation learning with unsupervised clustering and resource-efficient client selection. …”
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Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data by Seung-Hwan Choi, Dawn An, Inho Lee, Suwoong Lee

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A Fast Prediction Model of Supercritical Airfoils Based on Deep Operator Network and Variational Autoencoder Considering Physical Constraints by Mengxin Liu, Yunjia Yang, Chenyu Wu, Yufei Zhang

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Representing particles’ motion patterns in microfluidic imaging platform using deep variational embeddings by Tianqi Hong, Meimei Peng, Marek Smieja, Qiyin Fang

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Robust Synthetic Data Generation for Sequential Financial Models Using Hybrid Variational Autoencoder–Markov Chain Monte Carlo Architectures by Francesco Bruni Prenestino, Enrico Barbierato, Alice Gatti

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Vibration-Based Anomaly Detection in Industrial Machines: A Comparison of Autoencoders and Latent Spaces by Luca Radicioni, Francesco Morgan Bono, Simone Cinquemani

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