2 papers
cs.LG2026
PCAE: Learning Ordered Representations in Latent Space for Intrinsic Dimension Estimation via Principal Component Autoencoder
Qipeng Zhan, Zhuoping Zhou, Zexuan Wang +1
Autoencoders have long been considered a nonlinear extension of Principal Component Analysis (PCA). Prior studies have demonstrated that linear autoencoders (LAEs) can recover the…
cs.LG2025
Multi-Scale Geometric Autoencoder
Qipeng Zhan, Zhuoping Zhou, Zexuan Wang +1
Autoencoders have emerged as powerful models for visualization and dimensionality reduction based on the fundamental assumption that high-dimensional data is generated from a low-d…