4 citations · 6 across the 4 of their papers we have counts for
4 papers · 1 filter
A Full Bayesian Approach to Sparse Network Inference using Heterogeneous Datasets
Junyang Jin, Ye Yuan, Jorge Goncalves
Network inference has been attracting increasing attention in several fields, notably systems biology, control engineering and biomedicine. To develop a therapy, it is essential to…
High Precision Variational Bayesian Inference of Sparse Linear Networks
Junyang Jin, Ye Yuan, Jorge Goncalves
Sparse networks can be found in a wide range of applications, such as biological and communication networks. Inference of such networks from data has been receiving considerable at…
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…
Sparse Bayesian Inference of Multivariable ARX Networks
J. Jin, Y. Yuan, A. Webb +1
Increasing attention has recently been given to the inference of sparse networks. In biology, for example, most molecules only bind to a small number of other molecules, leading to…