collaborators

10 papers

cs.RO2026

HoloMotion-1 Technical Report

Maiyue Chen, Kaihui Wang, Bo Zhang +7

In this report, we present HoloMotion-1, a humanoid motion foundation model for zero-shot whole-body motion tracking. A key innovation of HoloMotion-1 is to scale control-policy tr…

cs.LG2026

MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification

Stephan Goerttler, Yucheng Wang, Emadeldeen Eldele +2

Recent advancements in machine learning-based signal analysis, coupled with open data initiatives, have fuelled efforts in automatic sleep stage classification. Despite the prolife…

cs.LG2026

Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation

Yubo Hou, Mohamed Ragab, Yucheng Wang +5

Accurate Remaining Useful Life (RUL) prediction without labeled target domain data is a critical challenge, and domain adaptation (DA) has been widely adopted to address it by tran…

cs.LG2026

A Unified Shape-Aware Foundation Model for Time Series Classification

Zhen Liu, Yucheng Wang, Boyuan Li +4

Foundation models pre-trained on large-scale source datasets are reshaping the traditional training paradigm for time series classification. However, existing time series foundatio…

eess.SP2025

Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification

Stephan Goerttler, Yucheng Wang, Fei He +1

Despite significant advances in deep learning-based sleep stage classification, the clinical adoption of automatic classification models remains slow. One key challenge is the lack…

cs.LG2025

Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends

Yucheng Wang, Mohamed Ragab, Yubo Hou +3

Remaining Useful Life (RUL) prediction for turbofan engines plays a vital role in predictive maintenance, ensuring operational safety and efficiency in aviation. Although data-driv…