A supervised variational autoencoder framework for dimensionality reduction and predictive modeling in high-dimensional socioeconomic data by Pei Xue, Tianshun Li

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Low-carbon optimization scheduling of IES based on enhanced diffusion model for scenario deep generation by Danhao Wang, Daogang Peng, Dongmei Huang, Huirong Zhao, Bogang Qu

Subjects: “…Variational Autoencoder…”
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Attention-driven multi-model architecture for unbalanced network traffic intrusion detection via extreme gradient boosting by Oluwadamilare Harazeem Abdulganiyu, Taha Ait Tchakoucht, Ahmed El Hilali Alaoui, Yakub Kayode Saheed

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Source-Free Domain Adaptation Framework for Rotary Machine Fault Diagnosis by Hoejun Jeong, Seungha Kim, Donghyun Seo, Jangwoo Kwon

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GenCoder++: A Protocol-Aware and Adversarially Robust Adaptive Intrusion Detection Framework for Hybrid CAN-Ethernet Vehicular Networks by Mikhail Smolin

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Enhanced Interpretable Forecasting of Cryptocurrency Prices Using Autoencoder Features and a Hybrid CNN-LSTM Model by Wajeeha Badar, Shabana Ramzan, Ali Raza, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

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Discrete variational autoencoders for synthetic nighttime visible satellite imagery by Mickell D. Als, David Tomarov, Steve Easterbrook

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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

Subjects: “…variational autoencoders…”
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Bias-Aware Generative AI for fair customer segmentation: a VAE and BIRCH clustering approach by Shivranjani Bharatbhai Gajjar, Vivekanand Mishra

Subjects: “…Variational autoencoders (VAE)…”
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A synthetic data-driven machine learning approach for athlete performance attenuation prediction by Mauricio C. Cordeiro, Ciaran O. Cathain, Ciaran O. Cathain, Lorcan Daly, Lorcan Daly, David T. Kelly, David T. Kelly, Thiago B. Rodrigues

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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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Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods by Zhishui You, Yuzhu Guo, Xiulei Zhang, Yifan Zhao

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Population synthesis with deep generative model: a joint household-individual approach by Abdoul Razac Sané, Rachid Belaroussi, Pierre Hankach, Pierre-Olivier Vandanjon

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SincVAE: A new semi-supervised approach to improve anomaly detection on EEG data using SincNet and variational autoencoder by Andrea Pollastro, Francesco Isgrò, Roberto Prevete

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Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects by Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim

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Harnessing dual variational autoencoders to decode microbe roles in diseases for traditional medicine discovery by Qing Ye, Yaxin Sun, Yaxin Sun, Yaxin Sun

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Impact of Normalization Techniques on Synthetic Load Profile Generation Using Deep Generative Models by Luis H. T. Bandoria, Walquiria N. Silva, Madson C. De Almeida

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GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data by Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen

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Exploration of Generative Neural Networks for Police Facial Sketches by Nerea Sádaba-Campo, Hilario Gómez-Moreno

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Exploring the Frontier: Generative AI Applications in Online Consumer Behavior Analytics by Takuma Kimura

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