22 citations · 67 across the 15 of their papers we have counts for
15 papers
Anomaly Detection with Ensemble of Encoder and Decoder
Xijuan Sun, Di Wu, Arnaud Zinflou +1
Hacking and false data injection from adversaries can threaten power grids' everyday operations and cause significant economic loss. Anomaly detection in power grids aims to detect…
Adaptive Aggregation for Safety-Critical Control
Huiliang Zhang, Di Wu, Benoit Boulet
Safety has been recognized as the central obstacle to preventing the use of reinforcement learning (RL) for real-world applications. Different methods have been developed to deal w…
Meta-Reinforcement Learning for Building Energy Management System
Huiliang Zhang, Di Wu, Arnaud Zinflou +1
The building sector is one of the largest contributors to global energy consumption. Improving its energy efficiency is essential for reducing operational costs and greenhouse gas…
Time Series Anomaly Detection via Reinforcement Learning-Based Model Selection
Jiuqi Elise Zhang, Di Wu, Benoit Boulet
Time series anomaly detection has been recognized as of critical importance for the reliable and efficient operation of real-world systems. Many anomaly detection methods have been…
An Early Fault Detection Method of Rotating Machines Based on Multiple Feature Fusion with Stacking Architecture
Wenbin Song, Di Wu, Weiming Shen +1
Early fault detection (EFD) of rotating machines is important to decrease the maintenance cost and improve the mechanical system stability. One of the key points of EFD is developi…
Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection
Wenbin Song, Di Wu, Weiming Shen +1
Early fault detection (EFD) of rolling bearings can recognize slight deviation of the health states and contribute to the stability of mechanical systems. In practice, very limited…