1 code implementation • 14 Jun 2023 • 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.
1 code implementation • 26 Mar 2021 • Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
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.
2 code implementations • 19 Jun 2020 • Gregory W. Gundersen, Michael Minyi Zhang, Barbara E. Engelhardt
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.