technologynetworks

Multiomics Data Integration With Machine Learning: Methods, Tools, and Biological Applications

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...
GitHub

Sentinel ️ — Agentic Quant Risk & Forensic Accounting Engine

ML IsolationForest + PyTorch autoencoder anomaly detection · supervised stress-day classifier (logistic + random forest) · semi-supervised label propagation · PCA + KMeans + Marchenko-Pastur denoising ...
GitHub

HyperGuard AI — Hybrid Intelligent Malware Detection Framework

Research-grade hybrid malware detection system combining Random Forest, XGBoost, and a Deep Neural Network in a weighted ensemble, with an Autoencoder for zero-day anomaly detection — featuring SHAP ...
IEEE

Xinmin Zhang

Deep Learning,Soft Sensor,Long Short-term Memory,Root Mean Square Error,Variation In Quality,Fault Diagnosis,Gated Recurrent Unit,Neural Network,Stacked Autoencoder,Training Set,Validation ...
IEEE

Bing Song

False Alarm Rate,Fault Diagnosis,Process Monitoring,Canonical Correlation Analysis,Control Limits,Fault Diagnosis Method,Incipient Fault,Incipient Fault Detection ...
Frontiers

Adversarial attacks detection for network intrusion detection systems using outlier-filtered principal component analysis

To address the need for a reconstruction-error-based adversarial detection solution that has better performance characteristics prior to the actual principal component analysis (PCA) construction step ...