NO. | Beijing Time (UTC+8) | Local Time | Type | Presentation Topic | Speaker | Affiliation / Organization |
---|---|---|---|---|---|---|
1 | 11:00-11:25 | 11:00-11:25 | Invited Talk |
Causal structural learning for improving HIV testing and treatment access |
Yifan Jiang | |
2 | 11:25-11:50 | 11:25-11:50 | Invited Talk |
Learning Network Properties without Network Data -- A Correlated Network Scale-up Model |
Xiaoyue Niu | |
3 | 11:50-12:15 | 11:50-12:15 | Invited Talk |
婚姻状况变化率的贝叶斯估计与预测 |
Junni Zhang | |
4 | 12:15-12:40 | 12:15-12:40 | Invited Talk |
Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations |
Zhenke Wu | University of Michigan, Ann Arbor |
NO. | Beijing Time (UTC+8) | Local Time | Type | Presentation Topic | Speaker | Affiliation / Organization |
---|---|---|---|---|---|---|
1 | 14:00-14:25 | 14:00-14:25 | Invited Talk |
Individual-centered partial information in social networks |
Xiao Han | |
2 | 14:25-14:50 | 14:25-14:50 | Invited Talk |
Estimating the Number of Communities with Individual-centered Partial Information |
Qing Yang | |
3 | 14:50-15:15 | 14:50-15:15 | Invited Talk |
SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals |
Fan Yang | |
4 | 15:15-15:40 | 15:15-15:40 | Invited Talk |
Spectral gap and edge universality of dense random regular graphs |
Yukun He |
NO. | Beijing Time (UTC+8) | Local Time | Type | Presentation Topic | Speaker | Affiliation / Organization |
---|---|---|---|---|---|---|
1 | 16:00-16:25 | 16:00-16:25 | Invited Talk |
Flexible Functional Treatment Effect Estimation |
Raymond K. W. Wong | Texas A&M University |
2 | 16:25-16:50 | 16:25-16:50 | Invited Talk |
Interpoint-Ranking Sign Covariance for Test of Independence |
Kehui Chen | University of Pittsburgh |
3 | 16:50-17:15 | 16:50-17:15 | Invited Talk |
Causal Inference on Distribution Functions |
Zhenhua Lin | National University of Singapore |
4 | 17:15-17:40 | 17:15-17:40 | Invited Talk |
Theory of functional principal components analysis for noisy and discretely observed data |
Hang Zhou |