Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models. - Jaewoo Park 002; Murali Haran (J. Comput. Graph. Stat., 2021)

Bayesian model selection for high-dimensional Ising models, with applications to educational data. - Jaewoo Park 002; Ick-Hoon Jin; Michael Schweinberger (Comput. Stat. Data Anal., 2022)

Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data. - Jaewoo Park 002; Yeseul Jeon; Minsuk Shin; Minjeong Jeon; Ick-Hoon Jin (J. Comput. Graph. Stat., 2022)

A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets. - Benjamin Seiyon Lee; Jaewoo Park 002 (Technometrics, 2023)

Fast Computer Model Calibration using Annealed and Transformed Variational Inference. - Dongkyu Derek Cho; Won Chang; Jaewoo Park 002 (J. Comput. Graph. Stat., 2025)

Density Estimation-Based Stein Variational Gradient Descent. - Jeongho Kim; Byungjoon Lee 003; Chohong Min; Jaewoo Park 002; Keunkwan Ryu (Cogn. Comput., 2025)

Posterior Contraction for Sparse Neural Networks in Besov Spaces with Intrinsic Dimensionality. - Kyeongwon Lee; Lizhen Lin; Jaewoo Park 002; Seonghyun Jeong (CoRR, 2025)