Suchergebnisse - conditioning variational autoencoder adaptive synthetic

MCVAE: A New Multi-Conditional Approach for Scalable Emergency Ad Hoc Network Design and Node Localization Using Generative Variational Autoencoder.

Autoren: Jabbar, M. A. A. Abbas, A. R. Ghani, R. F.

Quelle: International Journal of Engineering Transactions C: Aspects; Jun2026, Vol. 39 Issue 6, p1390-1401, 12p

Schlagwörter: AD hoc computer networks, EMERGENCY management, REAL-time computing, AUTOENCODERS, PROBABILISTIC generative models, WIRELESS communications, SCALABILITY

Text-Conditioned Diffusion-Based Synthetic Data Generation for Turbine Engine Sensor Analysis and RUL Estimation.

Autoren: Mora-de-León, Luis Pablo Solís-Martín, David Galán-Páez, Juan et al.

Quelle: Machines; May2025, Vol. 13 Issue 5, p374, 25p

Schlagwörter: REMAINING useful life, GENERATIVE adversarial networks, PRINCIPAL components analysis, AUTOENCODERS, STATISTICAL correlation

ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking.

Autoren: Hsu, Chih-Yu Chang, Chih-Yin Chen, Yin-Chi et al.

Quelle: Sensors (14248220); Apr2025, Vol. 25 Issue 7, p2321, 26p

Schlagwörter: DIGITAL technology, DIGITAL watermarking, COPYRIGHT, DATA security, DETECTOR circuits

Adaptive Neural Network System for Detecting Unauthorised Intrusions Based on Real-Time Traffic Analysis.

Autoren: Vladov, Serhii Vysotska, Victoria Lytvyn, Vasyl et al.

Quelle: Computation; Sep2025, Vol. 13 Issue 9, p221, 42p

Schlagwörter: INTRUSION detection systems (Computer security), ANOMALY detection (Computer security), KALMAN filtering, LATENT variables, INTERNET security, TRAFFIC monitoring, MACHINE learning, INTELLIGENT networks

Adaptive Ensemble Framework With Synthetic Sampling for Tackling Class Imbalance Problem.

Autoren: Sasirekha, R. Kanisha, B.

Quelle: Engineering Reports; Apr2025, Vol. 7 Issue 4, p1-10, 10p

Schlagwörter: ENSEMBLE learning, GENERATIVE adversarial networks, LEARNING strategies, HEART diseases, ALGORITHMS

Anomaly Detection for Charging Piles Based on Conditional Variational Autoencoder.

Autoren: Wang, Chuanjun Lu, Yinyu Wang, Mingxin et al.

Quelle: International Transactions on Electrical Energy Systems; 9/23/2025, Vol. 2025, p1-12, 12p

Schlagwörter: ELECTRIC vehicles, SUPERVISED learning, PROBABILISTIC generative models, OUTLIER detection, SIGNAL detection, DISTRIBUTION (Probability theory), INFRASTRUCTURE (Economics)

CSCVAE-NID: A Conditionally Symmetric Two-Stage CVAE Framework with Cost-Sensitive Learning for Imbalanced Network Intrusion Detection.

Autoren: Wang, Zhenyu Yu, Xuejun

Quelle: Entropy; Nov2025, Vol. 27 Issue 11, p1086, 22p

Schlagwörter: INTRUSION detection systems (Computer security), DATA augmentation, CLASSIFICATION, MACHINE learning

Sequential SAR-to-Optical Image Translation.

Autoren: Wei, Jingbo Zhou, Huan Ke, Peng et al.

Quelle: Remote Sensing; Jul2025, Vol. 17 Issue 13, p2287, 19p

Schlagwörter: SYNTHETIC aperture radar, TRANSFORMER models, FEATURE extraction

EEG-to-EEG: Scalp-to-Intracranial EEG Translation Using a Combination of Variational Autoencoder and Generative Adversarial Networks.

Autoren: Abdi-Sargezeh, Bahman Shirani, Sepehr Valentin, Antonio et al.

Quelle: Sensors (14248220); Jan2025, Vol. 25 Issue 2, p494, 19p

Schlagwörter: GENERATIVE adversarial networks, AUTOENCODERS, EPILEPTIFORM discharges, ELECTROENCEPHALOGRAPHY, DATA mapping

Conditioned quantum-assisted deep generative surrogate for particle-binary vector indicating thecalorimeter interactions.

Autoren: Toledo-Marín, J. Quetzalcóatl Gonzalez, Sebastian Jia, Hao et al.

Quelle: NPJ Quantum Information; 7/7/2025, Vol. 11 Issue 1, p1-15, 15p

Schlagwörter: PARTICLES (Nuclear physics), PHYSICAL sciences, LARGE Hadron Collider, QUANTUM annealing, COLLISIONS (Nuclear physics), CALORIMETERS

Conditional Variational Autoencoder with Inverse Normalization Transformation on Synthetic Data Augmentation in Software Effort Estimation.

Autoren: Marco, Robert Syed Ahmad, Sharifah Sakinah Ahmad, Sabrina

Quelle: International Journal of Intelligent Engineering & Systems; 2022, Vol. 15 Issue 3, p366-381, 16p

Schlagwörter: DATA augmentation, MANN Whitney U Test, STANDARD deviations, K-nearest neighbor classification, SOFTWARE engineering

Geografische Kategorien: CHINA

An enhancement of machine learning model performance in disease prediction with synthetic data generation.

Autoren: Kannan, M. Umamaheswari, D. Manimekala, B. et al.

Quelle: Scientific Reports; 9/29/2025, Vol. 15 Issue 1, p1-21, 21p

Schlagwörter: MACHINE learning, DATA augmentation, ARTIFICIAL intelligence, PREDICTION models, DATA quality

CAESAR: A Unified Framework for Foundation and Generative Models for Efficient Compression of Scientific Data.

Autoren: Li, Xiao Zhu, Liangji Lee, Jaemoon et al.

Quelle: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 16, p8977, 24p

Schlagwörter: DATA compression, DATA reduction, INTERPOLATION, LATENT variables, EMPIRICAL research

TVAE-3D: Efficient multi-view 3D shape reconstruction with diffusion models and transformer based VAE.

Autoren: Sajid, Muhammad Malik, Kaleem Razzaq Khan, Ali Haider et al.

Quelle: Cluster Computing; Nov2025, Vol. 28 Issue 13, p1-22, 22p

Schlagwörter: COMPUTER vision, THREE-dimensional imaging, PROBABILISTIC generative models, TRANSFORMER models, POINT cloud, LATENT variables

Zero-Shot Learning for S&P 500 Forecasting via Constituent-Level Dynamics: Latent Structure Modeling Without Index Supervision.

Autoren: Noh, Yoonjae Kim, Sangjin

Quelle: Mathematics (2227-7390); Sep2025, Vol. 13 Issue 17, p2762, 17p

Schlagwörter: STANDARD & Poor's 500 Index, FORECASTING, MACROECONOMICS, ECONOMIC competition, IMPLICIT learning, LATENT structure analysis, AUTOENCODERS

Geografische Kategorien: UNITED States

Symmetry-Aware CVAE-ACGAN-Based Feature Generation Model and Its Application in Fault Diagnosis.

Autoren: Ma, Long Liu, Yingjie Zhang, Yue et al.

Quelle: Symmetry (20738994); Jun2025, Vol. 17 Issue 6, p947, 20p

Schlagwörter: CONVOLUTIONAL neural networks, GENERATIVE adversarial networks, STANDARD deviations, AUTOENCODERS, DEEP learning

Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods.

Autoren: You, Zhishui Guo, Yuzhu Zhang, Xiulei et al.

Quelle: Sensors (14248220); May2025, Vol. 25 Issue 10, p3178, 55p

Schlagwörter: GENERATIVE adversarial networks, NATURAL language processing, COMPUTER vision, DECODING algorithms, BRAIN-computer interfaces

Developing an Explainable Variational Autoencoder (VAE) Framework for Accurate Representation of Local Circulation in Taiwan.

Autoren: Hsieh, Min‐Ken Wu, Chien‐Ming

Quelle: Journal of Geophysical Research. Atmospheres; 6/28/2024, Vol. 129 Issue 12, p1-20, 20p

Schlagwörter: ARTIFICIAL neural networks, TRANSITION flow, REDUCED-order models, WEATHER forecasting, WIND speed, TYPHOONS

Geografische Kategorien: TAIWAN

Conditional VAE for personalized neurofeedback in cognitive training.

Autoren: Tibermacine, Imad Eddine Russo, Samuele Scarano, Gianmarco et al.

Quelle: PLoS ONE; 10/31/2025, Vol. 20 Issue 10, p1-28, 28p

Schlagwörter: MACHINE learning, FEATURE extraction, NEUROPHYSIOLOGY, ARTIFICIAL intelligence, COGNITIVE training, ROUTINE diagnostic tests

VTAE: Variational Transformer Autoencoder With Manifolds Learning.

Autoren: Shamsolmoali, Pourya Zareapoor, Masoumeh Zhou, Huiyu et al.

Quelle: IEEE Transactions on Image Processing; 2023, Vol. 32, p4486-4500, 15p

Schlagwörter: RIEMANNIAN manifolds, RIEMANNIAN metric, COMPUTER vision, AUTOENCODERS, FEATURE extraction, LATENT variables