Balancing Performance and Fairness in Explainable AI for Anomaly Detection in Distributed Power Plants Monitoring
Fuente:
arXiv
Saved in:
| Main Authors: | Niyonkuru, Corneille, Atemkeng, Marcellin, Nguegnang, Gabin Maxime, Fadja, Arnaud Nguembang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Clustering-Based Low-Rank Matrix Approximation for Medical Image Compression
by: Hamlomo, Sisipho, et al.
Published: (2025)
by: Hamlomo, Sisipho, et al.
Published: (2025)
An Empirical Study of Machine Learning Robustness and Scalability for Imbalanced Tabular Clinical Data in Emergency and Critical Care
by: Brima, Yusuf, et al.
Published: (2025)
by: Brima, Yusuf, et al.
Published: (2025)
Unsupervised anomaly detection in large-scale estuarine acoustic telemetry data
by: Zaza, Siphendulwe, et al.
Published: (2025)
by: Zaza, Siphendulwe, et al.
Published: (2025)
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging
by: Hamlomo, Sisipho, et al.
Published: (2024)
by: Hamlomo, Sisipho, et al.
Published: (2024)
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
by: Brima, Yusuf, et al.
Published: (2026)
by: Brima, Yusuf, et al.
Published: (2026)
Bridging visual saliency and large language models for explainable deep learning in medical imaging
by: Nguezet, Paul Valery, et al.
Published: (2026)
by: Nguezet, Paul Valery, et al.
Published: (2026)
Explainable Condition Monitoring via Probabilistic Anomaly Detection Applied to Helicopter Transmissions
by: Ugolini, Aurelio Raffa, et al.
Published: (2026)
by: Ugolini, Aurelio Raffa, et al.
Published: (2026)
Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment
by: Adjokatse, Isaac Tettey, et al.
Published: (2026)
by: Adjokatse, Isaac Tettey, et al.
Published: (2026)
Detecting the Unexpected: AI-Driven Anomaly Detection in Smart Bridge Monitoring
by: Jaiswal, Rahul, et al.
Published: (2026)
by: Jaiswal, Rahul, et al.
Published: (2026)
Fairness-aware Anomaly Detection via Fair Projection
by: Xiao, Feng, et al.
Published: (2025)
by: Xiao, Feng, et al.
Published: (2025)
Fair Anomaly Detection For Imbalanced Groups
by: Wu, Ziwei, et al.
Published: (2024)
by: Wu, Ziwei, et al.
Published: (2024)
An Optimised Greedy-Weighted Ensemble Framework for Financial Loan Default Prediction
by: Nortey, Ezekiel Nii Noye, et al.
Published: (2026)
by: Nortey, Ezekiel Nii Noye, et al.
Published: (2026)
Balancing Fairness and Performance in Healthcare AI: A Gradient Reconciliation Approach
by: Wang, Xiaoyang, et al.
Published: (2025)
by: Wang, Xiaoyang, et al.
Published: (2025)
Explainable Unsupervised Anomaly Detection with Random Forest
by: Harvey, Joshua S., et al.
Published: (2025)
by: Harvey, Joshua S., et al.
Published: (2025)
Leaf-Based Plant Disease Detection and Explainable AI
by: Sagar, Saurav, et al.
Published: (2023)
by: Sagar, Saurav, et al.
Published: (2023)
Explainable Anomaly Detection for Industrial IoT Data Streams
by: Paupério, Ana Rita, et al.
Published: (2025)
by: Paupério, Ana Rita, et al.
Published: (2025)
Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis
by: Hamlomo, Sisipho, et al.
Published: (2026)
by: Hamlomo, Sisipho, et al.
Published: (2026)
Risk-Based Thresholding for Reliable Anomaly Detection in Concentrated Solar Power Plants
by: Estievenart, Yorick, et al.
Published: (2025)
by: Estievenart, Yorick, et al.
Published: (2025)
Explainable AI for Fair Sepsis Mortality Predictive Model
by: Chang, Chia-Hsuan, et al.
Published: (2024)
by: Chang, Chia-Hsuan, et al.
Published: (2024)
MIXAD: Memory-Induced Explainable Time Series Anomaly Detection
by: Kim, Minha, et al.
Published: (2024)
by: Kim, Minha, et al.
Published: (2024)
Root Causing Prediction Anomalies Using Explainable AI
by: Vishnampet, Ramanathan, et al.
Published: (2024)
by: Vishnampet, Ramanathan, et al.
Published: (2024)
Power Interpretable Causal ODE Networks: A Unified Model for Explainable Anomaly Detection and Root Cause Analysis in Power Systems
by: Sun, Yue, et al.
Published: (2026)
by: Sun, Yue, et al.
Published: (2026)
Explainable Anomaly Detection for Electric Vehicles Charging Stations
by: Cederle, Matteo, et al.
Published: (2025)
by: Cederle, Matteo, et al.
Published: (2025)
Towards Explainable Anomaly Detection in Shared Mobility Systems
by: Isgandarov, Elnur, et al.
Published: (2025)
by: Isgandarov, Elnur, et al.
Published: (2025)
AXIS: Explainable Time Series Anomaly Detection with Large Language Models
by: Lan, Tian, et al.
Published: (2025)
by: Lan, Tian, et al.
Published: (2025)
Unifying Explainable Anomaly Detection and Root Cause Analysis in Dynamical Systems
by: Sun, Yue, et al.
Published: (2025)
by: Sun, Yue, et al.
Published: (2025)
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle
by: Deck, Luca, et al.
Published: (2024)
by: Deck, Luca, et al.
Published: (2024)
FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
by: Liu, Pengxi, et al.
Published: (2025)
by: Liu, Pengxi, et al.
Published: (2025)
An Explainable AI based approach for Monitoring Animal Health
by: Jana, Rahul, et al.
Published: (2025)
by: Jana, Rahul, et al.
Published: (2025)
Explainable Time Series Anomaly Detection using Masked Latent Generative Modeling
by: Lee, Daesoo, et al.
Published: (2023)
by: Lee, Daesoo, et al.
Published: (2023)
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection
by: Naser, MZ, et al.
Published: (2024)
by: Naser, MZ, et al.
Published: (2024)
Knowledge-Augmented Explainable and Interpretable Learning for Anomaly Detection and Diagnosis
by: Atzmueller, Martin, et al.
Published: (2024)
by: Atzmueller, Martin, et al.
Published: (2024)
Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts
by: Zhang, Guangyi, et al.
Published: (2026)
by: Zhang, Guangyi, et al.
Published: (2026)
Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)
by: Wang, Shouju, et al.
Published: (2025)
AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum
by: Balasubramanian, Prasasthy, et al.
Published: (2025)
by: Balasubramanian, Prasasthy, et al.
Published: (2025)
Explainable AI in Big Data Fraud Detection
by: Jain, Ayush, et al.
Published: (2025)
by: Jain, Ayush, et al.
Published: (2025)
Adaptive and Explainable AI Agents for Anomaly Detection in Critical IoT Infrastructure using LLM-Enhanced Contextual Reasoning
by: Sharma, Raghav, et al.
Published: (2025)
by: Sharma, Raghav, et al.
Published: (2025)
Anomaly Detection in High-Dimensional Bank Account Balances via Robust Methods
by: Maddanu, Federico, et al.
Published: (2025)
by: Maddanu, Federico, et al.
Published: (2025)
Balanced Edge Pruning for Graph Anomaly Detection with Noisy Labels
by: Wang, Zhu, et al.
Published: (2024)
by: Wang, Zhu, et al.
Published: (2024)
Explainable AI For Early Detection Of Sepsis
by: Thakur, Atharva, et al.
Published: (2025)
by: Thakur, Atharva, et al.
Published: (2025)
Similar Items
-
Clustering-Based Low-Rank Matrix Approximation for Medical Image Compression
by: Hamlomo, Sisipho, et al.
Published: (2025) -
An Empirical Study of Machine Learning Robustness and Scalability for Imbalanced Tabular Clinical Data in Emergency and Critical Care
by: Brima, Yusuf, et al.
Published: (2025) -
Unsupervised anomaly detection in large-scale estuarine acoustic telemetry data
by: Zaza, Siphendulwe, et al.
Published: (2025) -
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging
by: Hamlomo, Sisipho, et al.
Published: (2024) -
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
by: Brima, Yusuf, et al.
Published: (2026)