3 papers
cs.LG2025
A Family of Kernelized Matrix Costs for Multiple-Output Mixture Neural Networks
Bo Hu, José C. PrÃncipe
Pairwise distance-based costs are crucial for self-supervised and contrastive feature learning. Mixture Density Networks (MDNs) are a widely used approach for generative models and…
cs.LG2025
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making
Shujian Yu, Hongming Li, Sigurd Løkse +2
The Cauchy-Schwarz (CS) divergence was developed by PrÃncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional d…
cs.LG2024
Kernel Operator-Theoretic Bayesian Filter for Nonlinear Dynamical Systems
Kan Li, José C. PrÃncipe
Motivated by the surge of interest in Koopman operator theory, we propose a machine-learning alternative based on a functional Bayesian perspective for operator-theoretic modeling…