Yan Bao

Missing data imputation using unsupervised learning for multi-sourced heterogeneous data in bridge structural health monitoring

Comparisons with the state-of-the-art methods, including K-nearest neighbour, ridge regression, and random forest, demonstrate that the mask-trained AE/VAE provides stable performance across diverse missing patterns without requiring repeated model training, offering a practical solution for heterogeneous bridge SHM da...