3 papers
cs.LG2025
Dynamic Graph-Like Learning with Contrastive Clustering on Temporally-Factored Ship Motion Data for Imbalanced Sea State Estimation in Autonomous Vessel
Kexin Wang, Mengna Liu, Xu Cheng +3
Accurate sea state estimation is crucial for the real-time control and future state prediction of autonomous vessels. However, traditional methods struggle with challenges such as…
cs.LG2025
Prototype-based Heterogeneous Federated Learning for Blade Icing Detection in Wind Turbines with Class Imbalanced Data
Lele Qi, Mengna Liu, Xu Cheng +3
Wind farms, typically in high-latitude regions, face a high risk of blade icing. Traditional centralized training methods raise serious privacy concerns. To enhance data privacy in…
cs.LG2024
An End-to-End Model for Time Series Classification In the Presence of Missing Values
Pengshuai Yao, Mengna Liu, Xu Cheng +4
Time series classification with missing data is a prevalent issue in time series analysis, as temporal data often contain missing values in practical applications. The traditional…