Publications
My publications, as in my CV; also available in BibTeX. My software is hosted on GitHub.
Articles
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Yurinskii’s coupling for martingales
M. D. Cattaneo, R. P. Masini and W. G. Underwood, 2025
Annals of Statistics, forthcoming
arXiv:2210.00362 -
Uniform inference for kernel density estimators with dyadic data
M. D. Cattaneo, Y. Feng and W. G. Underwood, 2024
Journal of the American Statistical Association, 119(548), 2695–2708
doi:10.1080/01621459.2023.2272785
arXiv:2201.05967 -
Motif-based spectral clustering of weighted directed networks
W. G. Underwood, A. Elliott and M. Cucuringu, 2020
Applied Network Science 5, 62
doi:10.1007/s41109-020-00293-z
arXiv:2004.01293 -
Simple Poisson PCA: an algorithm for (sparse) feature extraction with simultaneous dimension determination
L. Smallman, W. G. Underwood and A. Artemiou, 2019
Computational Statistics 35, 559-577
doi:10.1007/s00180-019-00903-0
Preprints
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Sharp anti-concentration inequalities for extremum statistics via copulas
M. D. Cattaneo, R. P. Masini and W. G. Underwood, 2025
arXiv:2502.07699 -
Inference with Mondrian random forests
M. D. Cattaneo, J. M. Klusowski and W. G. Underwood, 2024
arXiv:2310.09702
Working papers
- Higher-order extensions to the Lindeberg method
M. D. Cattaneo, R. P. Masini and W. G. Underwood
Presentations and conferences
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London Symposium on Information Theory, Cambridge, May 2025
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International Conference on Statistics and Data Science, Nice, December 2024
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Statistics Seminar, University of Pittsburgh, February 2024
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Statistics Seminar, University of Illinois Urbana-Champaign, January 2024
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Statistics Seminar, University of Michigan, January 2024
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PhD Poster Session, Two Sigma Investments, New York, July 2023
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Statistical Foundations of Data Science and their Applications, Princeton University, May 2023
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Research Symposium, Two Sigma Investments, New York, June 2022
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Statistics Laboratory, Princeton University, September 2021
Software
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tex-fmt
LaTeX formatter written in Rust
W. G. Underwood, 2024
Available on GitHub -
MondrianForests
Mondrian random forests in Julia
W. G. Underwood, 2023
Available on GitHub -
DyadicKDE
Dyadic kernel density estimation in Julia
W. G. Underwood, 2022
Available on GitHub -
motifcluster
Motif-based spectral clustering of directed networks in R, Python and Julia
W. G. Underwood and A. Elliott, 2020
doi:10.5281/zenodo.3832400
Available on GitHub, CRAN, and PyPI