4 papers
CausalGDP: Causality-Guided Diffusion Policies for Reinforcement Learning
Xiaofeng Xiao, Xiao Hu, Yang Ye +1
Reinforcement learning (RL) has achieved remarkable success in a wide range of sequential decision-making problems. Recent diffusion-based policies further improve RL by modeling c…
Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations
Xiaofeng Xiao, Bo Shen, Xubo Yue
Nowadays, as AI-driven manufacturing becomes increasingly popular, the volume of data streams requiring real-time monitoring continues to grow. However, due to limited resources, i…
Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning
Cheoljoon Jeong, Xubo Yue, Seokhyun Chung
Many failure mechanisms of machinery are closely related to the behavior of condition monitoring (CM) signals. To achieve a cost-effective preventive maintenance strategy, accurate…
Explainable Federated Bayesian Causal Inference and Its Application in Advanced Manufacturing
Xiaofeng Xiao, Khawlah Alharbi, Pengyu Zhang +2
Causal inference has recently gained notable attention across various fields like biology, healthcare, and environmental science, especially within explainable artificial intellige…