1 citations · 1 across the 1 of their papers we have counts for
4 papers
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior
Anh Tong, Toan Tran, Hung Bui +1
Choosing a proper set of kernel functions is an important problem in learning Gaussian Process (GP) models since each kernel structure has different model complexity and data fitne…
Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems
Anh Tong, Jaesik Choi
Recent advances in Deep Gaussian Processes (DGPs) show the potential to have more expressive representation than that of traditional Gaussian Processes (GPs). However, there exists…
Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes
Jiyeon Han, Kyowoon Lee, Anh Tong +1
In the analysis of sequential data, the detection of abrupt changes is important in predicting future changes. In this paper, we propose statistical hypothesis tests for detecting…
Searching for Topological Symmetry in Data Haystack
Kallol Roy, Anh Tong, Jaesik Choi
Finding interesting symmetrical topological structures in high-dimensional systems is an important problem in statistical machine learning. Limited amount of available high-dimensi…