Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…Then, we introduce a variational information bottleneck (VIB)-assisted domain adaptation (DA) approach to enhance integrated deep learning and Lagrangian method (IDLA)’s adaptability across diverse network environments and conditions. …”
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Iterative Analysis of Nonlinear BBM Equations under Nonsingular Fractional Order Derivative by Gauhar Ali, Israr Ahmad, Kamal Shah, Thabet Abdeljawad

“…The concerned tool is formed when the Adomian decomposition method is coupled with some integral transform like Laplace. …”
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Enhancing Anomaly Detection Through Latent Space Manipulation in Autoencoders: A Comparative Analysis by Tomasz Walczyna, Damian Jankowski, Zbigniew Piotrowski

“…This study provides valuable insights into advancing machine learning methods for real-world applications and sets the stage for further refinement of autoencoder-based approaches.…”
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Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM. by Wei Liu, Sen Liu

“…To address the issue of low accuracy in existing remaining useful life (RUL) prediction algorithms for rolling bearings, this paper proposes a novel RUL prediction method based on the Beluga Whale Optimization (BWO) algorithm, Variational Mode Decomposition (VMD), an improved Convolutional Block Attention Module (CBAM*), and a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Smart furniture using radar technology for cardiac health monitoring by Ali Gharamohammadi, Mohammad Omid Bagheri, Serene Abu-Sardanah, Michael M. Y. R. Riad, Hajar Abedi, Ahmad Ansariyan, Kang Wang, Ashish Saragadam, Dmytro Chumachenko, Shahabeddin Abhari, Plinio Pelegrini Morita, Amir Khajepour, George Shaker

“…Experiment results demonstrate a maximum interbeat intervals (IBI) error of 30 milliseconds and an average relative error of 4.8% in heart rate estimation, showcasing the efficacy of the proposed method utilizing variational mode decomposition and a multi-bin approach.…”
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A Multi-Scale Unsupervised Feature Extraction Network with Structured Layer-Wise Decomposition by Yusuf Şevki Günaydın, Baha Şen

“…This study introduces a novel unsupervised multi-scale feature extraction framework based on a multi-branch auto-encoder architecture. The proposed method decomposes input images into smooth, detailed and residual components, using variational loss functions to ensure that each branch captures distinct and non-overlapping representations. …”
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Social-aware trajectory prediction using goal-directed attention networks with egocentric vision by Lia Astuti, Chui-Hong Chiu, Yu-Chen Lin, Ming-Chih Lin

“…This study presents a novel social-goal attention networks (SGANet) model that employs a vision-based multi-stacked neural network framework to predict multiple future trajectories for both homogeneous and heterogeneous road users. Unlike existing methods that focus solely on one dataset type and treat social interactions, temporal dynamics, destination point, and uncertainty behaviors independently, SGANet integrates these components into a unified multimodal prediction framework. …”
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Generalization of Beckmann’s Transformation for Traffic Assignment Models with Asymmetric Cost Functions by Matthieu Marechal, Louis de Grange

“…It is shown that this method is equivalent to the variational inequality approach. …”
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Latent Space Search-Based Adaptive Template Generation for Enhanced Object Detection in Bin-Picking Applications by Songtao Liu, Yaonan Zhu, Tadayoshi Aoyama, Masayuki Nakaya, Yasuhisa Hasegawa

“…Furthermore, we integrated our proposed method with YOLO, and the experimental results indicate that our method effectively improves YOLO’s detection performance.…”
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Measuring. Monitoring. Management. Control by F.G. Agayev, H.H. Asadov, M.E. Omarov, S.S. Aliyeva

“…The variational method was used to reach the formulated goal. …”

A new numerical technique to seek properties of the nonlinear oscillators by Jing-Yan Niu, Guang-Qing Feng

“…This new transformation coupled with the variational iteration method is highly effective for various nonlinear problems and offers a new window for wide applications. …”
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Modal Analysis of a Discrete System in the Form of a Rocket Launcher Installed on a Motor Vehicle by Zbigniew DZIOPA, Maciej NYCKOWSKI

“…A mathematical model was derived using the variational method on the basis of the assumed physical model. …”
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Quantum generative learning for high-resolution medical image generation by Amena Khatun, Kübra Yeter Aydeniz, Yaakov S Weinstein, Muhammad Usman

“…Integration of quantum computing in generative machine learning models has the potential to offer benefits such as training speed-up and superior feature extraction. …”
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Inverse Problem of Identifying a Time-Dependent Source Term in a Fractional Degenerate Semi-Linear Parabolic Equation by Maroua Nouar, Chattouh Abdeledjalil, Omar Mossa Alsalhi, Hamed Ould Sidi

“…The proof methodology is based on the Rothe method, where the variational formulation is discretized in time, and a priori estimates for discrete solutions are derived. …”
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The potential of generative AI with prostate-specific membrane antigen (PSMA) PET/CT: challenges and future directions by Islam Md Zobaer, Spiro Ergi, Yap Pew-Thian, Gorin Michael A., Rowe Steven P.

“…PSMA-PET imaging has demonstrated superior performance compared to conventional imaging methods by detecting PCa, its biochemical recurrence, and sites of metastasis with higher sensitivity and specificity. …”
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Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer by Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang

“…The method integrates multi-frequency sequence feature analysis and multi-point correction using the FEDformer model. …”
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Enhanced Noise Suppression in Partial Discharge Signals via SVD and VMD with Wavelet Thresholding by Hailong Wang, Yongliang Yao, Guangdong Zhang, Jidong Pan, Longlong Gao, Hai Jin, Chuang Wang

“…This article introduces an advanced denoising algorithm integrating SVD, variational mode decomposition (VMD), and wavelet thresholding to effectively address mixed noise in on-site power transformer assessments. …”
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Fault analysis of chemical equipment based on an improved hybrid model. by Wu Huiyong, Kuan Jiang, Wang Yanyu

“…The method combines Variational Mode Decomposition (VMD), Least Mean Squares (LMS) processing, an asymmetric attention mechanism, and a pre-activation ResNet-BiGRU model to create an efficient framework for multimodal data fusion and analysis. …”
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Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression by Askhat Diveev, Elena Sofronova, Nurbek Konyrbaev

“…The paper includes an example of solving the control synthesis problem for a mobile robot using a supervised machine learning method. A relatively new method of symbolic regression, the method of variational complete binary genetic programming, is studied and proposed for the solution of the control synthesis problem.…”
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Identification of Exposed Submarine Cable Status based on Optimized VMD-GAF-MCNN for Multi Sensor Fusion by WANG Wei, WANG Wendong, YOU Peng, XIAO Zexin, AN Bowen, CUI Guiyan

“…【Methods】The optimized VMD-GAF-MCNN method proposed in this paper integrates signal processing and deep learning techniques. …”
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