:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Rahal, Manal, Ahmed, Bestoun S., Renstrom, Roger, Stener, Robert, Wurtz, Albrecht
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.15719
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cross-household Transfer Learning Approach with LSTM-based Demand Forecasting
by: Rahal, Manal, et al.
Published: (2026)

Enhancing Machine Learning Performance through Intelligent Data Quality Assessment: An Unsupervised Data-centric Framework
by: Rahal, Manal, et al.
Published: (2025)

Prediction of Retention Time in Larger Antisense Oligonucleotide Datasets using Machine Learning
by: Rahal, Manal, et al.
Published: (2025)

End-to-End Data Quality-Driven Framework for Machine Learning in Production Environment
by: Bayram, Firas, et al.
Published: (2025)

Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
by: Bayram, Firas, et al.
Published: (2024)

Smart Manufacturing: MLOps-Enabled Event-Driven Architecture for Enhanced Control in Steel Production
by: Ahmed, Bestoun S., et al.
Published: (2025)

An Adaptive Metaheuristic Framework for Changing Environments
by: Ahmed, Bestoun S.
Published: (2024)

Data-Driven Energy Estimation for Virtual Servers Using Combined System Metrics and Machine Learning
by: Sangha, Amandip
Published: (2025)

Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods
by: Arweiler, Justus, et al.
Published: (2025)

Adaptive Data Quality Scoring Operations Framework using Drift-Aware Mechanism for Industrial Applications
by: Bayram, Firas, et al.
Published: (2024)

Research on Dynamic Data Flow Anomaly Detection based on Machine Learning
by: Wang, Liyang, et al.
Published: (2024)

Constrained Reinforcement Learning for Safe Heat Pump Control
by: Zhang, Baohe, et al.
Published: (2024)

Machine Learning-Driven Anomaly Detection for 5G O-RAN Performance Metrics
by: Azkaei, Babak, et al.
Published: (2025)

Real-Time Machine Learning for Embedded Anomaly Detection
by: Benmachiche, Abdelmadjid, et al.
Published: (2025)

Go-Explore for Residential Energy Management
by: Lu, Junlin, et al.
Published: (2024)

A Generic Machine Learning Framework for Fully-Unsupervised Anomaly Detection with Contaminated Data
by: Ulmer, Markus, et al.
Published: (2023)

Position: Untrained Machine Learning for Anomaly Detection by using 3D Point Cloud Data
by: Du, Juan, et al.
Published: (2025)

Physics-Guided Deep Learning for Heat Pump Stress Detection: A Comprehensive Analysis on When2Heat Dataset
by: Alam, Md Shahabub, et al.
Published: (2025)

Adaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection
by: Sameh, Ahmed, et al.
Published: (2025)

Quantifying and Predicting Residential Building Flexibility Using Machine Learning Methods
by: Salter, Patrick, et al.
Published: (2024)

Contextual Learning for Anomaly Detection in Tabular Data
by: King, Spencer, et al.
Published: (2025)

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data
by: Hasan, Nazmul, et al.
Published: (2024)

Building Machine Learning Challenges for Anomaly Detection in Science
by: Campolongo, Elizabeth G., et al.
Published: (2025)

On the Unknowable Limits to Prediction
by: Yan, Jiani, et al.
Published: (2024)

Quantum Machine Learning for Anomaly Detection in Consumer Electronics
by: Bhowmik, Sounak, et al.
Published: (2024)

A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems
by: Gomez, Pere Izquierdo, et al.
Published: (2023)

Early Detection of Water Stress by Plant Electrophysiology: Machine Learning for Irrigation Management
by: Buss, Eduard, et al.
Published: (2026)

Machine Learning for Anomaly Detection in Particle Physics
by: Belis, Vasilis, et al.
Published: (2023)

Federated Learning for Anomaly Detection in Maritime Movement Data
by: Graser, Anita, et al.
Published: (2025)

Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics
by: Oancea, Bogdan
Published: (2026)

AI-Powered Machine Learning Approaches for Fault Diagnosis in Industrial Pumps
by: Alghtus, Khaled M. A., et al.
Published: (2025)

Applied Machine Learning to Anomaly Detection in Enterprise Purchase Processes
by: Herreros-Martínez, A., et al.
Published: (2024)

Adversarial Sample Generation for Anomaly Detection in Industrial Control Systems
by: Mustafa, Abdul, et al.
Published: (2025)

XAI-Driven Machine Learning System for Driving Style Recognition and Personalized Recommendations
by: Sellal, Feriel Amel, et al.
Published: (2025)

KD-GAT: Combining Knowledge Distillation and Graph Attention Transformer for a Controller Area Network Intrusion Detection System
by: Frenken, Robert, et al.
Published: (2025)

Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications
by: Haug, Markus, et al.
Published: (2025)

Anomaly Detection with Machine Learning Algorithms in Large-Scale Power Grids
by: Gillioz, Marc, et al.
Published: (2026)

Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities
by: Qi, Jiaxing, et al.
Published: (2024)

Cybersecurity-Focused Anomaly Detection in Connected Autonomous Vehicles Using Machine Learning
by: Lebaku, Prathyush Kumar Reddy, et al.
Published: (2025)

SHIELD: Securing Healthcare IoT with Efficient Machine Learning Techniques for Anomaly Detection
by: Desai, Mahek, et al.
Published: (2025)