44 citations · 68 across the 12 of their papers we have counts for
Showing 2019Show all
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stat.ME2019★ 1 cited
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…
stat.ME2019★ 1 cited
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…
stat.ML2019
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…