WORKING PAPER：（*CORRESPONDING,#STUDENT SUPERVISED）

1. Liu D^#, Zhao C^#, He Y*, Guo Y, Liu L, Zhang X. Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data. Biometrics, revision under review. arXiv:2110.04516

2. He Y, Li Q^#, Hu Q, Liu L. Transfer Learning in High-dimensional Semi-parametric Graphical Models with Application to Brain Connectivity Analysis. Statistics in Medicine, under revision. arXiv:2112.13356

3. He Y, Kong X, Yu L, Zhao P. Quantile factor analysis for large-dimensional time series with statistical guarantee. arXiv:2006.08214

4. He Y, Kong X, Trapani L, Yu L. One-way or Two-way Factor Model for Matrix Sequences? arXiv:2110.01008 

5. He Y, Kong X, Trapani L, Yu L. Online Change-point Detection for Matrix-valued Time Series with Latent Two-way Factor Structure. arXiv:2112.13479

6. He Y, Kong X, Yu L, Zhang X, Zhao C^#. Statistical Inference for Large-dimensional Matrix Factor Model from Least Squares and Huber Loss Points of View. arXiv:2112.04186

7. Chen H^#, Guo Y, He Y*, Liu D^#, Liu L, Zhou X. Joint Learning of Multiple Differential Networks for Matrix-variate Data with Application to Brain Connectivity Alteration Detection. arXiv:2106.03334

8. Yu L, He Y, Zhang X, Zhu J. Network-Assisted Estimation for Large-dimensional Factor Model with Guaranteed Convergence Rate Improvement. arXiv:2001.10955.