57 citations · 165 across the 7 of their papers we have counts for
3 papers · 1 filter
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
Tong Teng, Jie Chen, Yehong Zhang +1
This paper presents a variational Bayesian kernel selection (VBKS) algorithm for sparse Gaussian process regression (SGPR) models. In contrast to existing GP kernel selection algor…
Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations
Jie Chen, Nannan Cao, Kian Hsiang Low +3
Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-t…
Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena
Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan +4
The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting conge…