Yiding Wang
Ph.D. Student in Mathematics, Xi'an Jiaotong University
Causal Discovery Brain Effective Connectivity Identifiability Continuous-Time Modeling
Research Interests
- Causal Discovery: Granger causality, structural causal models, constraint-based and score-based methods
- Brain Effective Connectivity: Dynamic effective connectivity networks, fMRI-based causal inference
- Identifiability: Identifiability conditions for causal models, structural identifiability analysis
- Continuous-Time Modeling: Neural ODE/SDE, latent continuous-time dynamics, irregular time series
Selected Publications
Continuous-Time Causal Distribution Learning with Identifiability for Brain Dynamic Effective Connectivity Inference [Abstract] [Code]
Yiding Wang, Longyun Chen, Chen Qiao
Medical Image Analysis, 112 (2026) 104124.Time-Reversal Enhanced Dynamic Causality Distribution Learning and Its Application in Identifying Dynamic ECNs in MCI Patients [Abstract] [Code]
Yiding Wang, Chao Jin, Jian Yang, Chen Qiao
IEEE Transactions on Biomedical Engineering, 73 (1) (2026).A Deep Spatio-Temporal Architecture for Dynamic ECN Analysis with Granger Causality based Causal Discovery [Abstract]
Faming Xu (co-first author), Yiding Wang (co-first author), Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Chen Qiao
Pattern Recognition, 172 (2026) 112346.EGCN-TSD: Explainable GCN for Time Series Data and Its Applications to the Study of Brain Development
Yiding Wang, Jiajia Li, Chen Qiao, Huiyu Zhou, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang
Neurocomputing, Revision.