62 citations · 153 across the 19 of their papers we have counts for
10 papers · 1 filter
Ordinary Differential Equation Models and their Computation Methods
Jaeyong Lee
In this article, I introduce the differential equation model and review their frequentist and Bayesian computation methods. A numerical example of the FitzHugh-Nagumo model is give…
Multivariate Lévy Adaptive B-Spline Regression
Sewon Park, Jaeyong Lee, Jeunghun Oh
We propose Multivariate Lévy Adaptive B-Spline Regression (MLABS), a Bayesian nonparametric regression model designed to capture nonlinear effects, interactions, and locally varyin…
Post-Processed Posteriors for Sparse Covariances and Its Application to Global Minimum Variance Portfolio
Kwangmin Lee, Jaeyong Lee
We consider Bayesian inference of sparse covariance matrices and propose a post-processed posterior. This method consists of two steps. In the first step, posterior samples are obt…
Bayesian Nonparametric Classification for Incomplete Data With a High Missing Rate: an Application to Semiconductor Manufacturing Data
Sewon Park, Kyeongwon Lee, Da-Eun Jeong +2
During the semiconductor manufacturing process, predicting the yield of the semiconductor is an important problem. Early detection of defective product production in the manufactur…
Identifiability of Covariance Kernels in the Gaussian Process Regression Model
Jaehoan Kim, Jaeyong Lee
Gaussian process regression (GPR) model is a popular nonparametric regression model. In GPR, features of the regression function such as varying degrees of smoothness and periodici…
Laplace-aided variational inference for differential equation models
Hyunjoo Yang, Jaeyong Lee
An ordinary differential equation (ODE) model, whose regression curves are a set of solution curves for some ODEs, poses a challenge in parameter estimation. The challenge, due to…