3 papers
cs.LG2026
PEFT-MuTS: A Multivariate Parameter-Efficient Fine-Tuning Framework for Remaining Useful Life Prediction based on Cross-domain Time Series Representation Model
En Fu, Yanyan Hu, Zengwang Jin +1
The application of data-driven remaining useful life (RUL) prediction has long been constrained by the availability of large amount of degradation data. Mainstream solutions such a…
cs.LG2025
Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning
En Fu, Yanyan Hu
Contrastive learning underpins most current self-supervised time series representation methods. The strategy for constructing positive and negative sample pairs significantly affec…
cs.LG2024
Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction
En Fu, Yanyan Hu, Kaixiang Peng +1
The problem of the Remaining Useful Life (RUL) prediction, aiming at providing an accurate estimate of the remaining time from the current predicting moment to the complete failure…