3 papers
stat.ML2025
Multi-View Oriented GPLVM: Expressiveness and Efficiency
Zi Yang, Ying Li, Zhidi Lin +2
The multi-view Gaussian process latent variable model (MV-GPLVM) aims to learn a unified representation from multi-view data but is hindered by challenges such as limited kernel ex…
stat.ML2025
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
Zhidi Lin, Ying Li, Feng Yin +2
Gaussian process state-space models (GPSSMs) offer a principled framework for learning and inference in nonlinear dynamical systems with uncertainty quantification. However, existi…
cs.LG2024
Scalable Random Feature Latent Variable Models
Ying Li, Zhidi Lin, Yuhao Liu +3
Random feature latent variable models (RFLVMs) represent the state-of-the-art in latent variable models, capable of handling non-Gaussian likelihoods and effectively uncovering pat…