Preprints
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Song, H., Wu, M.C.
Limitation of permutation-based differential correlation analysis. -
Song, H., Chen, H.
New graph-based multi-sample tests for high-dimensional and non-Euclidean data.
arXiv [R package: gTestsMulti] - Song, H., Chen, H.
Practical and powerful kernel-based change-point detection.
arXiv [R package: kerSeg] -
Song, H., Chen, H.
A fast and effective large-scale two-sample test based on kernels.
arXiv - Song, H., Chen, H.
Generalized kernel two-sample tests.
arXiv [R package: kerTests]
Publications
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Song, H., Ling, W., Zhao, N., Plantinga, A.M., Broedlow, C.A., Klatt, N.R.,
Hensley-McBain, T., Wu, M.C. (2023).
Accommodating multiple potential normalizations in microbiome associations studies.
BMC Bioinformatics, 24(1):22. -
Song, H., Liu, H., Wu, M.C. (2022).
A fast kernel independence test for cluster-correlated data.
Scientific Reports, 12(1):21659. -
Ling, W., Lu, J., Zhao, N., Lulla, A., Plantinga, A., Fu, W., Zhang, A., Liu, H.,
Song, H., Li, Z., Chen, J., Randolph, T., Koay, W., White, J., Launer, L., Fodor, A.,
Meyer, K., Wu, M.C. (2022).
Batch effects removal for microbiome data via conditional quantile regression.
Nature Communications, 13(1):5418. -
Song, H., Chen, H. (2022).
Asymptotic distribution-free change-point detection for data with repeated observations.
Biometrika, 109(3):783-798. [R package: gSeg] -
Song, H., Thiagarajan, J., Kailkhura, B. (2021).
Preventing failures by dataset shift detection in safety-critical graph applications.
Frontiers in Artificial Intelligence, 4:589632.