Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm by José Oscullo Lala, Nathaly Orozco Garzón, Henry Carvajal Mora, Diego Echeverria, José Vega-Sánchez, Takaaki Ohishi

“…This paper presents an enhanced methodology for modal analysis that combines Adaptive Variational Mode Decomposition (A-VMD) with Prony’s method. …”
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A Systematic Review of the Advances and New Insights into Copy Number Variations in Plant Genomes by Saimire Silaiyiman, Jiaxuan Liu, Jiaxin Wu, Lejun Ouyang, Zheng Cao, Chao Shen

“…Copy number variations (CNVs), as an important structural variant in genomes, are widely present in plants, affecting their phenotype and adaptability. …”
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Nonlinear Dynamic Process Monitoring Based on Discriminative Denoising Autoencoder and Canonical Variate Analysis by Jun Liang, Daoguang Liu, Yinxiao Zhan, Jiayu Fan

“…In this article, we present a novel process monitoring approach, CVA-<i>DisDAE</i>, which integrates an improved Denoising Autoencoder (<i>DAE</i>) with Canonical Variate Analysis (CVA) to address the challenges posed by dynamic behaviors and nonlinear relationships in industrial processes. …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

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Evaluating Spatio-Temporal Kriging with Machine Learning Considering the Sources of Spatio-Temporal Variation by Min Jeong, Hyeongmo Koo

“…Integrating spatio-temporal kriging with machine learning improves estimation accuracy by addressing complex spatial and temporal variations in spatio-temporal phenomena. …”
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A Study on the Variations in Chinese Character Libraries: A Case Study of Song Typeface by Fushi Chen, Xingzhou Han, Xingyu Duan, Yang Yang

“…Results: Leveraging Python-based tools, we replaced the traditional printing process with digital image rendering to conduct our analyses, employing both traditional overlay comparison methods and image differentiation techniques. Furthermore, we introduced an innovative metric to quantify character variation. …”
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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

“…In order to effectively identify malicious URLs, an enhanced deep learning‐based phishing detection approach has been proposed by integrating the strength of Variational Autoencoders (VAE) and deep neural networks (DNN). …”
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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

“…To establish a rapid prediction model mapping sound speed profiles (SSPs) to acoustic TL through controllable generation, this study proposes a hybrid framework that integrates a variational autoencoder (VAE) and a normalizing flow (Flow) through a two-stage training strategy. …”
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Deep plug-and-play denoising prior with total variation regularization for low-dose CT by Yinjin Ma, Yajuan Zhang, Lin Chen, Qiang Jiang, Fengjuan Shi, Biao Wei

“…We then train the DRBNet using a hybrid loss function combining L1 and multi-scale structural similarity (M-SSIM) losses, while regularizing the training with total variation (TV). After training, the DRBNet is integrated as a deep denoiser prior into a half-quadratic splitting-based method to solve the LDCT image denoising problem. …”
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Spatial variation of soil quality in key grain-producing areas of Qitai County, Xinjiang by FAN Zikang, WANG Chunxia, YU Jing, QIN Da, YANG Yuefa, WANG Hongxin

“…Classical statistical methods were used to analyze the correlations between indicators, and geostatistical methods were used to assess the spatial variation of each indicator. …”
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Variations in the concentration of subsoil gases and the atmospheric electric field prior to some earthquakes in Kamchatka by @Makarov, Evgenii O., Akbashev, Rinat R., Glukhov, Vitalii E.

“…A conclusion was made about the necessity of integrating various methods of recording geophysical fields, including direct measurements of crustal deformation, for the successful advancement of approaches to earthquake forecasting…”
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Latent profiles of youth social support: a study on variations and their impact on self-esteem by Jingxian Yu, Yuqin Guo, Yongqi Liang, Huan Peng, Na Li, Weisheng Gu, Hanjiao Liu

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Localising loci underlying complex trait variation using Regional Genomic Relationship Mapping. by Yoshitaka Nagamine, Ricardo Pong-Wong, Pau Navarro, Veronique Vitart, Caroline Hayward, Igor Rudan, Harry Campbell, James Wilson, Sarah Wild, Andrew A Hicks, Peter P Pramstaller, Nicholas Hastie, Alan F Wright, Chris S Haley

“…Motivated by studies that demonstrate that loci contributing to trait variation may contain a number of different alleles, we have developed an analytical approach termed Regional Genomic Relationship Mapping that, like linkage-based family methods, integrates variance contributed by founder gametes within a pedigree. …”
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Assessment of the temporal variations of surface water bodies in Dhaka City using Landsat imagery by Md Rayhan, Md Mahin Mobarrat, Maiesha Nujhat, Ronjan Kumar Paul, Md Khairul Amin

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Spectral Quadratic Variation Regularized Autoweighted Tensor Ring Decomposition for Hyperspectral Image Reconstruction by Xinwei Wan, Dan Li, Fanqiang Kong, Yanyan Lv, Qiang Wang

“…The effectiveness of model-based reconstruction methods can be promoted. In this article, a subspace-based model utilizing spectral quadratic variation regularized autoweighted tensor ring (TR) decomposition is proposed to explore the multiple-layer spatial&#x2013;spectral priors of HSI. …”
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Photon sensor-based monitoring of spatial variations in canopy FIPAR for crop growth assessment by Jian Wang, Zhenggui Zhang, Xin Li, Lu Feng, Xiaofei Li, Minghua Xin, Shiwu Xiong, Yingchun Han, Shijie Zhang, Xiaoyu Zhi, Beifang Yang, Guoping Wang, Yaping Lei, Zhanbiao Wang, Yabing Li

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Synergy and Effectiveness Evaluation of Carbon Policy and Government Subsidies: Variational Inequality Model Based on Supply Chain Network by Chao Wang, Hui Sun, Yuehu Wang

“…., production cost subsidies, low-carbon technology subsidies, and low-carbon product subsidies). By integrating these approaches, six distinct policy combinations were identified. …”
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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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Achieving excellent mechanical properties in CoNiCrMo multi-principal element alloys: A comprehensive approach integrating mean square atomic displacement and machine learning meth... by Yang Long, Wei Fang, Haoyang Yu, Tiexu Peng, Cong Li, Weiguang Liu, Chang Liu, Qinghe Jia, Yushui Chen, Jia Li, Fuxing Yin

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Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models by Chenling Xu, Romain Lopez, Edouard Mehlman, Jeffrey Regier, Michael I Jordan, Nir Yosef

“…In contrast to existing methods, scVI and scANVI integrate multiple datasets with a single generative model that can be directly used for downstream tasks, such as differential expression. …”
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