activity
20162022
most citedIntelligent Icing Detection Model of Wind Turbine Blades Based on SCADA data

4 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

stat.ML2022★ 2 cited

Bayesian Inference of Stochastic Dynamical Networks

Yasen Wang, Junyang Jin, Jorge Goncalves

Network inference has been extensively studied in several fields, such as systems biology and social sciences. Learning network topology and internal dynamics is essential to under…

cs.LG2021★ 4 cited

Intelligent Icing Detection Model of Wind Turbine Blades Based on SCADA data

Wenqian Jiang, Junyang Jin

Diagnosis of ice accretion on wind turbine blades is all the time a hard nut to crack in condition monitoring of wind farms. Existing methods focus on mechanism analysis of icing p…

eess.SY2019

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…

eess.SY2019

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…

eess.SY2016

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…

eess.SY2016

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…