9:30 - 9:50 breakfast
9:50 - 10:00 opening remarks
10:00 - 10:50 Paper Session I
- Linjun Huang, Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
- Peng Xu, Generative Quantum Machine Learning via Denoising Diffusion Probabilistic Models
- Zhiyuan Yu, Sampling from the Random Linear Model via Stochastic Localization Up to the AMP Threshold
- Kaihong Zhang, Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
10:50 - 11:00 break
11:00 - 12:00 Wijsman Lecture
- Bodhisattva Sen, Extending the Scope of Nonparametric Empirical Bayes
12:00 - 1:00 lunch
1:00 - 1:50 Paper Session II
- Arghya Chakraborty, Testing for Adverse Events in Post-marketing Surveillance
- ByeongJip Kim, A Hypothesis Testing for the Comparison of Two Multi-layer Networks: a Kernel-based Approach
- Sophie Larsen, Immune history influences SARS-CoV-2 booster impacts: the role of efficacy and redundancy
- Theren Williams, A Study on Restricted HMMs for Latent Class Attribute Transitionse
1:50 - 2:00 break
2:00 - 2:50 Paper Session III
- David Kim, Asymptotic Valid Permutation Test in Strongly Mixing Conditions
- Heman Leung, Online GMM for Time Series
- Yi Zhang, Another look at bandwidth-free inference: a sample splitting approach
2:45 - 3:00 break
3:00 - 3:50 Norton Session
- Hanjia Gao, Statistical Inference for Time Series via Sample Splitting
- Rentian Yao, Optimization over probability distributions with proximal gradient descent
3:50 - 4:00 break
4:00 - 5:00 Bohrer Lecture
- Judy Wang, Flexible Probabilistic Prediction for Non-Gaussian Spatial Processes
5:00 - 6:00 Award Presentations and Poster Session
6:00 - 8:00 Dinner
