1 citations · 3 across the 4 of their papers we have counts for
4 papers
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network
Rui Meng, Herbie Lee, Kristofer Bouchard
This paper presents an efficient variational inference framework for deriving a family of structured gaussian process regression network (SGPRN) models. The key idea is to incorpor…
Nonstationary Multivariate Gaussian Processes for Electronic Health Records
Rui Meng, Braden Soper, Herbert Lee +3
We propose multivariate nonstationary Gaussian processes for jointly modeling multiple clinical variables, where the key parameters, length-scales, standard deviations and the corr…
Hierarchical Hidden Markov Jump Processes for Cancer Screening Modeling
Rui Meng, Soper Braden, Jan Nygard +2
Hidden Markov jump processes are an attractive approach for modeling clinical disease progression data because they are explainable and capable of handling both irregularly sampled…
Regularized Sparse Gaussian Processes
Rui Meng, Herbert Lee, Soper Braden +1
Gaussian processes are a flexible Bayesian nonparametric modelling approach that has been widely applied but poses computational challenges. To address the poor scaling of exact in…