Search Results - (conditional OR conditioning) variational autoencoder（cae）

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor.

Authors: Asano, Takuma Izumi, Shintaro Kawaguchi, Hiroshi

Source: Frontiers in Digital Health; 2025, p1-12, 12p

Subject Terms: PATIENT monitoring equipment, BIOLOGICAL models, RESEARCH funding, SOUND spectrography, BIOMETRY, HEART beat, ELECTROCARDIOGRAPHY, SECURITY systems, TECHNOLOGY, PATIENT monitoring, MICROWAVES, WAVE analysis, ALGORITHMS

Conditional neural field latent diffusion model for generating spatiotemporal turbulence.

Authors: Du, Pan Parikh, Meet Hemant Fan, Xiantao et al.

Source: Nature Communications; 11/29/2024, Vol. 15 Issue 1, p1-22, 22p

Subject Terms: UNSTEADY flow, FLUID dynamics, LARGE eddy simulation models, TURBULENCE, TURBULENT flow

Asset Pricing via the Conditional Quantile Variational Autoencoder.

Authors: Yang, Xuanling Zhu, Zhoufan Li, Dong et al.

Source: Journal of Business & Economic Statistics; Apr2024, Vol. 42 Issue 2, p681-694, 14p

Subject Terms: PRICES, DISTRIBUTION (Probability theory), SHARPE ratio, FACTOR structure, CAPITAL assets pricing model, QUANTILES

Continual learning approaches for anomaly detection.

Authors: Pezze, Davide Dalle Anello, Eugenia Masiero, Chiara et al.

Source: Evolving Systems; Dec2025, Vol. 16 Issue 4, p1-20, 20p

A Modular Perspective on the Evolution of Deep Learning: Paradigm Shifts and Contributions to AI.

Authors: Wei, Yicheng Wang, Yifu Watada, Junzo

Source: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 19, p10539, 38p

Subject Terms: DEEP learning, ARTIFICIAL intelligence, OPTIMIZATION algorithms, RESEARCH methodology, SCALABILITY, LANGUAGE models, TECHNOLOGICAL innovations

Condition Monitoring Using a Latent Space of Variational Autoencoder Trained Only on a Healthy Machine.

Authors: Komorska, Iwona Puchalski, Andrzej

Source: Sensors (14248220); Nov2024, Vol. 24 Issue 21, p6825, 14p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, DISTRIBUTION (Probability theory), RANDOM variables, FAULT diagnosis, FEATURE extraction

A Survey of Traditional and Emerging Deep Learning Techniques for Non-Intrusive Load Monitoring.

Authors: Huzzat, Annysha Khwaja, Ahmed S. Alnoman, Ali A. et al.

Source: AI; Sep2025, Vol. 6 Issue 9, p213, 50p

Subject Terms: DEEP learning, ARTIFICIAL intelligence, SMART meters, ENERGY consumption, GENERATIVE artificial intelligence

Adaptive Variational Mode Decomposition and Principal Component Analysis-Based Denoising Scheme for Borehole Radar Data.

Authors: Yang, Ding Guo, Cheng Persico, Raffaele et al.

Source: Remote Sensing; Feb2025, Vol. 17 Issue 3, p525, 25p

Subject Terms: METAHEURISTIC algorithms, GROUND penetrating radar, HILBERT-Huang transform, PRINCIPAL components analysis, SIGNAL-to-noise ratio

Fast Prediction of Airfoil Aerodynamic Characteristics Based on a Combined Autoencoder.

Authors: Wang, Xu Qian, Weiqi Zhao, Tun et al.

Source: Symmetry (20738994); Jul2024, Vol. 16 Issue 7, p791, 17p

Subject Terms: WIND tunnel testing, LATENT variables, REYNOLDS number, AEROFOILS, NETWORK performance

Graph Representation Learning on Street Networks.

Authors: Neira, Mateo Murcio, Roberto

Source: ISPRS International Journal of Geo-Information; Aug2025, Vol. 14 Issue 8, p284, 18p

Subject Terms: REPRESENTATIONS of graphs, URBAN morphology, PATTERN perception, SPATIAL behavior, LATENT variables, ROAD construction, TRAFFIC patterns, CONVOLUTIONAL neural networks

Wood-species identification based on terahertz spectral data augmentation and pseudo-label guided deep clustering.

Authors: Wang, Yuan Wang, Zhi-Gang He, Yi-Hao et al.

Source: Wood Material Science & Engineering; Oct2024, Vol. 19 Issue 5, p1004-1014, 11p

Subject Terms: WOOD, DATA augmentation, MACHINE learning, PROBLEM solving, TERAHERTZ spectroscopy, GRISELINIA littoralis

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

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

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

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

Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications.

Authors: Kim, Sungil Kim, Tea-Woo Jo, Suryeom

Source: Journal of Petroleum Exploration & Production Technology; Feb2025, Vol. 15 Issue 2, p1-60, 60p

Deep Learning for Time Series Anomaly Detection: A Survey.

Authors: Zamanzadeh Darban, Zahra Webb, Geoffrey I. Pan, Shirui et al.

Source: ACM Computing Surveys; Jan2025, Vol. 57 Issue 1, p1-42, 42p

Subject Terms: ARTIFICIAL neural networks, ARTIFICIAL intelligence, REINFORCEMENT learning, CONVOLUTIONAL neural networks, GRAPH neural networks, DEEP learning, SUPERVISED learning

A novel 3D indoor localization method integrating deep spatial feature augmentation and attention-based denoising.

Authors: Liu, Chunyuan Yu, Xiaomin Wu, Peilong et al.

Source: Scientific Reports; 9/26/2025, Vol. 15 Issue 1, p1-16, 16p

Subject Terms: INDOOR positioning systems, DEEP learning, GENERATIVE adversarial networks, WIRELESS geolocation systems, SIGNAL denoising, SPACE perception

Autoencoder-Assisted Stacked Ensemble Learning for Lymphoma Subtype Classification: A Hybrid Deep Learning and Machine Learning Approach.

Authors: Ogundokun, Roseline Oluwaseun Owolawi, Pius Adewale Tu, Chunling et al.

Source: Tomography: A Journal for Imaging Research; Aug2025, Vol. 11 Issue 8, p91, 22p

Subject Terms: AUTOENCODERS, ENSEMBLE learning, DEEP learning, FEATURE extraction, CANCER diagnosis, HISTOPATHOLOGY, MACHINE learning

A review of artificial intelligence applications in wind turbine health monitoring.

Authors: Sasinthiran, Abirami Gnanasekaran, Sakthivel Ragala, Ramesh

Source: International Journal of Sustainable Energy; Dec2024, Vol. 43 Issue 1, p1-35, 35p

Subject Terms: ARTIFICIAL intelligence, SIGNAL processing, MACHINE learning, WIND turbines, WIND power

An Intelligent Model of Anomaly Detection and Anomaly Localization in Images Using Hybrid Heuristic Adaptive Multiscale Attention-Based DenseNet and Cascaded Variational Autoencoder.

Authors: Jenifer, L. Leena Devaki, K.

Source: International Journal of Pattern Recognition & Artificial Intelligence; Sep2024, Vol. 38 Issue 11, p1-42, 42p

Subject Terms: OPTIMIZATION algorithms, INDUSTRIALISM, FRAUD, IMAGE processing, ALGORITHMS

Data-driven nonlinear parametric model order reduction framework using deep hierarchical variational autoencoder.

Authors: Lee, SiHun Lee, Sangmin Jang, Kijoo et al.

Source: Engineering with Computers; Aug2024, Vol. 40 Issue 4, p2385-2400, 16p

F0-consistent many-to-many non-parallel voice conversion via conditional autoencoder

Authors: Qian, Kaizhi Jin, Zeyu Hasegawa-Johnson, Mark et al.

Index Terms: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning, Computer Science - Sound, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2004.07370