Výsledky vyhľadávania - stack sparse autoencoder deep learning model (sage)~

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

Autori: Jnaini, Abdellah Koulali, Mohammed-Amine

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

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

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

Autori: Zhou, Zhecheng Du, Zhenya Jiang, Xin a ďalší

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

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

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

Autori: Yang, Meihong Wang, Xiaoli Cai, Binlei a ďalší

Zdroj: 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.

Autori: Wang, Zhina Chen, Yangyuan Ma, Hongming a ďalší

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

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

Deep learning model for recommendation system using web of things based knowledge graph mining.

Autori: Byeon, Haewon Chunduri, Venkata Narang, Geetika a ďalší

Zdroj: Service Oriented Computing & Applications; Mar2025, Vol. 19 Issue 1, p57-76, 20p

Graph-ensemble fusion for enhanced IoT intrusion detection: leveraging GCN and deep learning.

Autori: Mittal, Kajol Khurana Batra, Payal

Zdroj: Cluster Computing; Nov2024, Vol. 27 Issue 8, p10525-10552, 28p

Predmety: GRAPH neural networks, CONVOLUTIONAL neural networks, INFORMATION technology security, COMPUTER network security, DEEP learning, DATA distribution

Trustworthy AI-based Performance Diagnosis Systems for Cloud Applications: A Review.

Autori: Xin, Ruyue Wang, Jingye Chen, Peng a ďalší

Zdroj: ACM Computing Surveys; May2025, Vol. 57 Issue 5, p1-37, 37p

Predmety: ARTIFICIAL intelligence, ARTIFICIAL neural networks, SOFTWARE engineering, INFORMATION technology, HIGH performance computing, DEEP learning

Large language models facilitating modern molecular biology and novel drug development.

Autori: Liu, Xiao-huan Lu, Zhen-hua Wang, Tao a ďalší

Zdroj: Frontiers in Pharmacology; 2025, p1-19, 19p

Predmety: LANGUAGE models, INFORMATION technology, ARTIFICIAL intelligence, PROTEIN structure prediction, SCIENTIFIC communication

Probabilistic Graph Model Based Recommendation Algorithm for Material Selection in Self-directed Learning.

Autori: Zhiyong Qiu Yingjin Cui

Zdroj: SAGE Open; Apr-Jun2024, Vol. 14 Issue 2, p1-16, 16p

Predmety: SELF-managed learning (Personnel management), INFORMATION retrieval, ALGORITHMS, GRAPH theory, DATA analysis

A review of named entity recognition: from learning methods to modelling paradigms and tasks.

Autori: Seow, Wei Liang Chaturvedi, Iti Hogarth, Amber a ďalší

Zdroj: Artificial Intelligence Review; Oct2025, Vol. 58 Issue 10, p1-87, 87p

Deep Learning Models for Diagnosis of Schizophrenia Using EEG Signals: Emerging Trends, Challenges, and Prospects.

Autori: Ranjan, Rakesh Sahana, Bikash Chandra Bhandari, Ashish Kumar

Zdroj: Archives of Computational Methods in Engineering; May2024, Vol. 31 Issue 4, p2345-2384, 40p

Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning.

Autori: Dai, Wenfeng Wang, Yanhong Yan, Shuai a ďalší

Zdroj: Scientific Reports; 8/19/2025, Vol. 15 Issue 1, p1-17, 17p

Predmety: DRUG discovery, GRAPH neural networks, BIOINFORMATICS, DATA integration, WAVELETS (Mathematics), MACHINE learning, DATA quality, PROTEIN-protein interactions

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

Autori: Altay, Gönül Küçüksille, Ecir Uğur

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

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

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

Autori: Morone, Diego D'Antuono, Rocco

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

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

Deep learning modelling techniques: current progress, applications, advantages, and challenges.

Autori: Ahmed, Shams Forruque Alam, Md. Sakib Bin Hassan, Maruf a ďalší

Zdroj: Artificial Intelligence Review; Nov2023, Vol. 56 Issue 11, p13521-13617, 97p

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

Autori: Lee, SiHun Lee, Sangmin Jang, Kijoo a ďalší

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

Beginner-Friendly Review of Research on R-Based Energy Forecasting: Insights from Text Mining.

Autori: Kim, Minjoong Kim, Hyeonwoo Moon, Jihoon

Zdroj: Electronics (2079-9292); Sep2025, Vol. 14 Issue 17, p3513, 59p

Predmety: ENERGY consumption forecasting, TEXT mining, EMPIRICAL research, MACHINE learning, REPRODUCIBLE research, SCIENTIFIC language

Novel architecture for gated recurrent unit autoencoder trained on time series from electronic health records enables detection of ICU patient subgroups.

Autori: Merkelbach, Kilian Schaper, Steffen Diedrich, Christian a ďalší

Zdroj: Scientific Reports; 3/11/2023, Vol. 13 Issue 1, p1-22, 22p

Predmety: ELECTRONIC health records, INTENSIVE care units, TIME series analysis, DEEP learning, INDIVIDUALIZED medicine, VIDEO coding

A Hybrid Sparse-dense Defensive DNN Accelerator Architecture against Adversarial Example Attacks.

Autori: Wang, Xingbin Zhao, Boyan Su, Yulan a ďalší

Zdroj: ACM Transactions on Embedded Computing Systems; Sep2024, Vol. 23 Issue 5, p1-28, 28p

Predmety: RELIABILITY in engineering, RESOURCE management, SYSTEM safety, SYNCHRONIZATION, ARTIFICIAL intelligence

Progress and opportunities of foundation models in bioinformatics.

Autori: Li, Qing Hu, Zhihang Wang, Yixuan a ďalší

Zdroj: Briefings in Bioinformatics; Nov2024, Vol. 25 Issue 6, p1-20, 20p

Predmety: LANGUAGE models, COMPUTATIONAL biology, ARTIFICIAL intelligence, SEQUENCE analysis, SCIENTIFIC community