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Bayesian Non-linear Latent Variable Modeling via Random Fourier Features
Michael Minyi Zhang, Gregory W. Gundersen, Barbara E. Engelhardt
The Gaussian process latent variable model (GPLVM) is a popular probabilistic method used for nonlinear dimension reduction, matrix factorization, and state-space modeling. Inferen…
Active multi-fidelity Bayesian online changepoint detection
Gregory W. Gundersen, Diana Cai, Chuteng Zhou +2
Online algorithms for detecting changepoints, or abrupt shifts in the behavior of a time series, are often deployed with limited resources, e.g., to edge computing settings such as…
Latent variable modeling with random features
Gregory W. Gundersen, Michael Minyi Zhang, Barbara E. Engelhardt
Gaussian process-based latent variable models are flexible and theoretically grounded tools for nonlinear dimension reduction, but generalizing to non-Gaussian data likelihoods wit…