302 citations · 560 across the 11 of their papers we have counts for
11 papers
Information-Based Calibration of Uncertainty Quantification in Product-of-Experts Gaussian Process Models
Yean Hoon Ong, Paolo Barucca, Wei Pan +1
Gaussian process (GP) regression with a single global GP (GP-glo) incurs cubic computational cost, limiting scalability to large datasets. Product-of-experts GP models (GP-pro), wh…
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems
Hongpeng Zhou, Wei Pan
Discovering governing equations from data is critical for diverse scientific disciplines as they can provide insights into the underlying phenomenon of dynamic systems. This work p…
Data-driven Discovery of Cyber-Physical Systems
Ye Yuan, Xiuchuan Tang, Wei Pan +5
Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical…
Dynamic Network Reconstruction from Heterogeneous Datasets
Zuogong Yue, Johan Thunberg, Wei Pan +2
Performing multiple experiments is common when learning internal mechanisms of complex systems. These experiments can include perturbations to parameters or external disturbances.…
Mixed Neural Network Approach for Temporal Sleep Stage Classification
Hao Dong, Akara Supratak, Wei Pan +3
This paper proposes a practical approach to addressing limitations posed by use of single active electrodes in applications for sleep stage classification. Electroencephalography (…
On Identification of Sparse Multivariable ARX Model: A Sparse Bayesian Learning Approach
J. Jin, Y. Yuan, W. Pan +4
This paper begins with considering the identification of sparse linear time-invariant networks described by multivariable ARX models. Such models possess relatively simple structur…