Nonlinear Dynamic Process Monitoring Based on Discriminative Denoising Autoencoder and Canonical Variate Analysis by Jun Liang, Daoguang Liu, Yinxiao Zhan, Jiayu Fan

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Enzyme sequence optimisation via Gromov-Wasserstein Autoencoders integrating MSA techniques by Xuze Wang, Yangyang Li, Xiancong Hou, Hao Liu

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Variational graph autoencoder for reconstructed transcriptomic data associated with NLRP3 mediated pyroptosis in periodontitis by Pradeep K. Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila

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scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis by Mehrshad Sadria, Anita Layton

“…Here, we introduce scVAEDer, a scalable deep-learning model that combines the power of variational autoencoders and deep diffusion models to learn a meaningful representation that retains both global structure and local variations. …”
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Multi-Task Trajectory Prediction Using a Vehicle-Lane Disentangled Conditional Variational Autoencoder by Haoyang Chen, Na Li, Hangguan Shan, Eryun Liu, Zhiyu Xiang

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Ship Trajectory Prediction in Complex Waterways Based on Transformer and Social Variational Autoencoder (SocialVAE) by Pengyue Wang, Mingyang Pan, Zongying Liu, Shaoxi Li, Yuanlong Chen, Yang Wei

“…This study proposes a ship trajectory prediction model called ShipTrack-TVAE, which is based on a Variational Autoencoder (SocialVAE) and Transformer architecture. …”
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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

Subjects: “…anomaly detection;variational autoencoder;spike and slab distribution;deep support vector network…”
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Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder by Aashutosh Girish Boob, Shih-I Tan, Airah Zaidi, Nilmani Singh, Xueyi Xue, Shuaizhen Zhou, Teresa A. Martin, Li-Qing Chen, Huimin Zhao

“…To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. …”
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Individualized Estimation of Baseline Retinal Nerve Fiber Layer Thickness Using Conditional Variational Autoencoder by Ou Tan, PhD, Keke Liu, MD, Aiyin Chen, MD, Dongseok Choi, PhD, Jonathan C.H. Chan, MD, Bonnie N.K. Choy, MD, Kendrick C. Shih, MD, Jasper K.W. Wong, MD, Alex L.K. Ng, MD, Janice J.C. Cheung, MD, Michael Y. Ni, MD, Jimmy S.M. Lai, MD, Gabriel M. Leung, MD, Ian Y.H. Wong, MD, David Huang, MD, PhD

Subjects: “…Conditional variational autoencoder…”
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Disorder-specific neurodynamic features in schizophrenia inferred by neurodynamic embedded contrastive variational autoencoder model by Chaoyue Ding, Yuqing Sun, Kunchi Li, Sangma Xie, Hao Yan, Peng Li, Jun Yan, Jun Chen, Huiling Wang, Huaning Wang, Yunchun Chen, Yongfeng Yang, Luxian Lv, Hongxing Zhang, Lin Lu, Dai Zhang, Yaojing Chen, Zhanjun Zhang, Tianzi Jiang, Bing Liu

“…In this study, we integrated a neurodynamic model with the classical Contrastive Variational Autoencoder (CVAE) to extract and evaluate macro-scale SCZ-specific features, including subject-level, region-level parameters, and time-varying states. …”
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An Anomaly Detection Method for Multivariate Time Series Data Based on Variational Autoencoders and Association Discrepancy by Haodong Wang, Huaxiong Zhang

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A Case Study on Monolith to Microservices Decomposition with Variational Autoencoder-Based Graph Neural Network by Rokin Maharjan, Korn Sooksatra, Tomas Cerny, Yudeep Rajbhandari, Sakshi Shrestha

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Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets by Zihao Wang, Zeyu Wu, Minghua Deng

“…To address these challenges, we proposes a flexible integration framework based on Variational Autoencoder called scGCM. The main task of scGCM is to integrate single-cell multimodal mosaic data and eliminate batch effects. …”
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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

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Automated building typology clustering and identification using a variational autoencoder on digital land cadastres by Jaime de-Miguel-Rodriguez, M.V. Requena-Garcia-Cruz, E. Romero-Sánchez, A. Morales-Esteban

Subjects: “…Variational autoencoder (VAE)…”
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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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Design of an integrated model using deep reinforcement learning and Variational Autoencoders for enhanced quantum security by Harshala Shingne, Diptee Chikmurge, Priya Parkhi, Poorva Agrawal

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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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A multi-class hybrid variational autoencoder and vision transformer model for enhanced plant disease identification by Folasade Olubusola Isinkaye, Michael Olusoji Olusanya, Ayobami Andronicus Akinyelu

“…To overcome these issues, we propose a hybrid model with the potential to combine Variational Autoencoders and Vision Transformers for enhanced accuracy and robustness of plant disease classification. …”
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Novel cancer subtyping method guided by tumor-normal sample in latent space of transcriptomic variational autoencoder by Hongzhi Wang, Yu Zhang, Dandan Zhang, Min Luo

“…To address this gap, we introduce VaDTN (Variational Autoencoder–Derived Tumor-to-Normal), a pan-cancer framework that integrates transcriptomic data from both tumor and normal samples into a unified latent space. …”
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