Publications

Preprints/Submitted:

• Park, J. and Gaynanova, I. (2026+) Fr'echet regression of multivariate distributions with nonparanormal transport. arXiv:2603.07014.
• Shao, E., Park, J., Punjabi, N., Jiang, H, and Gaynanova, I. (2026+) Fast distance computation between multivariate distributions via nonparanormal Transport. arXiv:2603.00322.
• Park, J., Park, C., Ahn, J. (2026+) A geometry-preserving framework for sufficient dimension reduction of compositional data. arXiv:2509.05563. Python codes.
• Park, J., Kok, N., and Gaynanova, I. (2026+) Beyond fixed thresholds: optimizing summaries of wearable device data via piecewise linearization of quantile functions. arXiv:2501.11777.

Peer-reviewed articles:

• Yeon, K., Gao, F., Kim, R., Lee, D., Park, J., Brown, D.A., and Park, C. (2026+) ``A Bayesian Approach to Semi-Supervised Domain Adaptation in Streaming Data.’’ Journal of Statistical Computation and Simulation, Accepted.
• Park, J., Ahn, J., and Park, C. (2023) Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data, Proceedings of the 40th International Conference on Machine Learning (ICML). Github.
• Kang, I., Choi, H., Yoon, Y.-J., Park, J., Kwon, S.-S., and Park, C. (2023), Frechet Distance-Based Cluster Analysis for Multi-Dimensional Functional Data, Statistics and Computing, 33(4), 75.
• Park, J., Yoon, C., Park, C., and Ahn, J. (2022), Kernel Methods for Radial Transformed Compositional Data with Many Zeros, Proceedings of the 39th International Conference on Machine Learning (ICML).