Search Results for author:
Found 3 papers, 3 papers with code
Bayesian Non-linear Latent Variable Modeling via Random Fourier Features
The Gaussian process latent variable model (GPLVM) is a popular probabilistic method used for nonlinear dimension reduction, matrix factorization, and state-space modeling.
Active multi-fidelity Bayesian online changepoint detection
We propose a multi-fidelity approach that makes cost-sensitive decisions about which data fidelity to collect based on maximizing information gain with respect to changepoints.
Latent variable modeling with random features
By approximating a nonlinear relationship between the latent space and the observations with a function that is linear with respect to random features, we induce closed-form gradients of the posterior distribution with respect to the latent variable.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
