Search Results - stack autoencoder (sage)

Autoencoder-based confidence score for item preknowledge detection.

Authors: Pan, Yiqin

Source: Behaviormetrika; Jul2025, Vol. 52 Issue 2, p317-342, 26p

Subject Terms: AUTOENCODERS, DEEP learning, PRIOR learning, SIMULATION methods & models, DETECTION algorithms, SIGNAL detection, TEST design

VTAE: Variational Transformer Autoencoder With Manifolds Learning.

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

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

A new automatic machine learning based hyperparameter optimization for workpiece quality prediction.

Authors: Wen, Long Ye, Xingchen Gao, Liang

Source: Measurement & Control (0020-2940); Aug2021, Vol. 54 Issue 7/8, p1088-1098, 11p

Subject Terms: MACHINE learning, FORECASTING, PREDICTION models, WARMUP, MANUFACTURING industries

Full stack optimization of microservice architecture: systematic review and research opportunity.

Authors: Yang, Meihong Wang, Xiaoli Cai, Binlei et al.

Source: Cluster Computing; Dec2025, Vol. 28 Issue 15, p1-29, 29p

Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines.

Authors: Wang, Zhina Chen, Yangyuan Ma, Hongming et al.

Source: Frontiers in Pharmacology; 2025, p1-12, 12p

Subject Terms: GRAPH neural networks, ARTIFICIAL intelligence, AUTOENCODERS, DRUG target, TRADITIONAL medicine

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

Authors: Jahangir, Raiyan Islam, Muhammad Nazrul Islam, Md. Shofiqul et al.

Source: BMC Cardiovascular Disorders; 4/7/2025, Vol. 25 Issue 1, p1-14, 14p

Subject Terms: BOOSTING algorithms, ARTIFICIAL intelligence, MACHINE learning, PRINCIPAL components analysis, SURVIVAL rate

GAM-MDR: probing miRNA–drug resistance using a graph autoencoder based on random path masking.

Authors: Zhou, Zhecheng Du, Zhenya Jiang, Xin et al.

Source: Briefings in Functional Genomics; Jul2024, Vol. 23 Issue 4, p475-483, 9p

Subject Terms: DEEP learning, GENE expression, MICRORNA, ACQUISITION of data, DISEASE progression, THERAPEUTICS

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

CVGAE: A Self-Supervised Generative Method for Gene Regulatory Network Inference Using Single-Cell RNA Sequencing Data.

Authors: Liu, Wei Teng, Zhijie Li, Zejun et al.

Source: Interdisciplinary Sciences: Computational Life Sciences; Dec2024, Vol. 16 Issue 4, p990-1004, 15p

Subject Terms: GRAPH neural networks, MULTILAYER perceptrons, GENE expression, RNA sequencing, GAUSSIAN distribution

Practical and Scalable ML-Driven Cloud Performance Debugging With Sage.

Authors: Gan, Yu Liang, Mingyu Dev, Sundar et al.

Source: IEEE Micro; Jul/Aug2022, Vol. 42 Issue 4, p27-36, 10p

Subject Terms: DEBUGGING, CLOUD computing, ROOT cause analysis, SAGE

Colloidal systems as experimental platforms for physics-informed machine learning.

Authors: Kang, Namhee Joo, Yeonseo An, Hyosung et al.

Source: Nanoscale Horizons; Dec2025, Vol. 10 Issue 12, p3270-3289, 20p

An EEG-based machine learning framework for diagnosing acute sleep deprivation.

Authors: Kumar, Daya Narayan, Apurva Lalgudi Ganesan, Saptharishi

Source: Frontiers in Physiology; 2025, p1-13, 13p

Subject Terms: SLEEP deprivation, MACHINE learning, ELECTROENCEPHALOGRAPHY, MEDICAL care, DEEP learning, COGNITIVE ability, CLASSIFICATION algorithms, DIAGNOSIS

Prediction of performance parameters of a hermetic reciprocating compressor applying an artificial neural network.

Authors: Bacak, Aykut Çolak, Andaç Batur Dalkılıç, Ahmet Selim

Source: Proceedings of the Institution of Mechanical Engineers: Part E: Journal of Process Mechanical Engineering (Sage Publications, Ltd.); Dec2025, Vol. 239 Issue 6, p3528-3539, 12p

Emerging frontiers in SERS-integrated optical waveguides: advancing portable and ultra-sensitive detection for trace liquid analysis.

Authors: Gao, Danheng Liu, Jiahao Liu, Xiao et al.

Source: Light: Science & Applications; 11/26/2025, Vol. 14 Issue 1, p1-27, 27p

Quantum-Inspired Cross-Attention Alignment for Turkish Scientific Abstractive Summarization.

Authors: Altay, Gönül Küçüksille, Ecir Uğur

Source: Electronics (2079-9292); Nov2025, Vol. 14 Issue 22, p4474, 38p

Subject Terms: TEXT summarization, LOW-resource languages, QUANTUM theory, MATHEMATICS, QUANTUM computing

Towards Sustainable Buildings and Energy Communities: AI-Driven Transactive Energy, Smart Local Microgrids, and Life Cycle Integration.

Authors: Ożadowicz, Andrzej

Source: Energies (19961073); Nov2025, Vol. 18 Issue 21, p5668, 31p

Subject Terms: SUSTAINABLE buildings, MICROGRIDS, CLEAN energy, CARBON dioxide mitigation, ENERGY management, OPERATIONS research

Graph neural networks: Historical backgrounds, present revolutions, and conventionalization for the future.

Authors: Maghdid, Sozan S. Rashid, Tarik A. Askar, Shavan K.

Source: International Journal of Data Science & Analytics; Nov2025, Vol. 20 Issue 6, p5237-5299, 63p

AI-based hardware and software tools in microscopy to boost research in immunology and virology.

Authors: Morone, Diego D'Antuono, Rocco

Source: Frontiers in Immunology; 2025, p1-29, 29p

Subject Terms: ARTIFICIAL intelligence, IMMUNOLOGY, DATA analysis, FLUORESCENCE, VIROLOGY, OPEN source software, MICROSCOPY, IMAGE processing

Do LLMs Offer a Robust Defense Mechanism Against Membership Inference Attacks on Graph Neural Networks?

Authors: Jnaini, Abdellah Koulali, Mohammed-Amine

Source: Computers (2073-431X); Oct2025, Vol. 14 Issue 10, p414, 20p

Subject Terms: GRAPH neural networks, PRIVACY, DEEP learning, LANGUAGE models, DATA privacy

Theoretical Bases of Methods of Counteraction to Modern Forms of Information Warfare.

Authors: Bakirov, Akhat Suleimenov, Ibragim

Source: Computers (2073-431X); Oct2025, Vol. 14 Issue 10, p410, 76p

Subject Terms: INFORMATION warfare, DISINFORMATION, INTERNET security, INFORMATION resources management, DIGITAL technology, COGNITIVE bias, NETWORK theory (Statistical physics), ARTIFICIAL intelligence