Publications

My publications, as in my CV; also available in BibTeX. My software is hosted on GitHub.

Articles

• 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

• Inference with Mondrian Random Forests
  M. D. Cattaneo, J. M. Klusowski and W. G. Underwood, 2024
  Annals of Statistics, reject and resubmit
  arXiv:2310.09702
  

• Yurinskii’s Coupling for Martingales
  M. D. Cattaneo, R. P. Masini and W. G. Underwood, 2024
  Annals of Statistics, revise and resubmit
  arXiv:2210.00362
  

Working papers

• Higher-order extensions to the Lindeberg method
  M. D. Cattaneo, R. P. Masini and W. G. Underwood
  

• Adaptive Mondrian Random Forests
  M. D. Cattaneo, R. Chandak, J. M. Klusowski and W. G. Underwood
  

Presentations and conferences

• International Conference on Statistics and Data Science, Nice, December 2024

• Statistics Seminar, University of Pittsburgh, February 2024

• Statistics Seminar, University of Illinois Urbana-Champaign, January 2024

• Statistics Seminar, University of Michigan, January 2024

• PhD Poster Session, Two Sigma Investments, New York, July 2023

• Statistical Foundations of Data Science and their Applications, Princeton University, May 2023

• Research Symposium, Two Sigma Investments, New York, June 2022

• Statistics Laboratory, Princeton University, September 2021

Software

• 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