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cs.LG2025
A Family of Kernelized Matrix Costs for Multiple-Output Mixture Neural Networks
Bo Hu, José C. Príncipe
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.LG2024
Kernel Operator-Theoretic Bayesian Filter for Nonlinear Dynamical Systems
Kan Li, José C. Príncipe
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…
cs.LG2023★ 5 cited
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 Príncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional di…