4 citations · 6 across the 6 of their papers we have counts for
6 papers
Cluster-Aware Conformal Calibration for Spatio-Temporal Distributional Prediction
Gooyoung Kim, Chae Young Lim, Wen-Ting Wang +2
DeepKriging-style models, such as Spatio-Temporal DeepKriging, improve scalability through basis-function embeddings and stochastic gradient learning; however, fixed regular-grid s…
Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors
Wen-Ting Wang, Wei-Ying Wu, Hao-Yun Huang +1
We present the Spatial Adapter, a parameter-efficient post-hoc layer that equips any frozen first-stage predictor with a structured spatial representation of its residual field and…
DeepKriging on the global Data
Hao-Yun Huang, Wen-Ting Wang, Ping-Hsun Chiang +1
The increasing availability of large-scale global datasets has generated a demand for scalable spatial prediction methods defined on spherical domains. Classical spatial models tha…
Spatial Regression With Multiplicative Errors, and Its Application With Lidar Measurements
Hojun You, Wei-Ying Wu, Chae Young Lim +2
Multiplicative errors in addition to spatially referenced observations often arise in geodetic applications, particularly in surface estimation with light detection and ranging (Li…
Regularized Nonlinear Regression with Dependent Errors and its Application to a Biomechanical Model
Hojun You, Kyubaek Yoon, Wei-Ying Wu +2
A biomechanical model often requires parameter estimation and selection in a known but complicated nonlinear function. Motivated by observing that data from a head-neck position tr…
Regularized Nonlinear Regression for Simultaneously Selecting and Estimating Key Model Parameters
Kyubaek Yoon, Hojun You, Wei-Ying Wu +8
In system identification, estimating parameters of a model using limited observations results in poor identifiability. To cope with this issue, we propose a new method to simultane…