Published & Accepted

* Contributed equally or listed in alphabetical order

1. Liu, M., and Lopes, M.E. Robust Max Statistics for High-Dimensional Inference, To appear: Statistica Sinica, 2026+. [arxiv]

2. Kang, Y., Liu, M., Yi, B., Lyu, J., Zhang, Z., Zhou, D., and Li, Y. Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions. ICLR 2026 (accepted). [arxiv]

Preprints

* Contributed equally or listed in alphabetical order

1. Liu, M.*, Zhou, D.*, and Chen, H. (2024). Generalized Independence Test for Modern Data. [arxiv] [Github]

2. Cai, Z.*, Fei, W.*, Liu, M.*, and Zhou, D.* (2025). MATES: Multi-view Aggregated Two-Sample Test.

3. Zhu, Q.*, Liu, M.*, Han, Y., and Zhou, D. (2025). WISE: A Weighted Similarity Aggregation Test for Serial Independence. [arxiv] [R package]

4. Vu, M.D.*, Liu, M.*, and Zhou, D. (2025). A Trainable Centrality Framework for Modern Data. [arxiv]

5. Liu, M., Wang, S. and Lopes, M.E. (2026). A Goodness-of-Fit Test for Independent Component Models in High Dimensions. [arxiv] [Github]

6. Liu, M., and Chen, H. (2026). Graph-Based Change-Point Detection for Partially Observed High-Dimensional Data. [arxiv]

Software

• R package: SimIndep.
  Developed for implementing the Weighted Information Similarity Aggregation (WISE) test for detecting serial dependence.

• R package: MATES.
  Developed for implementing the Multi-view Aggregated Two-Sample (MATES) test for testing equality of two multivariate distributions.