Publications
High‐dimensional principal component analysis with heterogeneous missingness
– Journal of the Royal Statistical Society Series B: Statistical Methodology
(2022)
(DOI: 10.1111/rssb.12550)
High‐dimensional principal component analysis with heterogeneous missingness
– Journal of the Royal Statistical Society: Series B (Statistical Methodology)
(2022)
(DOI: 10.1111/rssb.12550)
High-dimensional changepoint estimation with heterogeneous missingness
– Journal of the Royal Statistical Society Series B (Statistical Methodology)
(2022)
84,
1023
(DOI: 10.1111/rssb.12540)
A Unifying Tutorial on Approximate Message Passing
– Foundations and Trends® in Machine Learning
(2022)
abs/2105.02180,
335
(DOI: 10.1561/2200000092)
Optimal nonparametric testing of Missing Completely At Random, and its
connections to compatibility
(2022)
Nonparametric, tuning‐free estimation of S‐shaped functions
– Journal of the Royal Statistical Society Series B: Statistical Methodology
(2022)
84,
1324
(DOI: 10.1111/rssb.12481)
Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission.
– Nature communications
(2022)
13,
751
(DOI: 10.1038/s41467-021-27942-w)
Isotonic regression with unknown permutations: Statistics, computation and adaptation
– The Annals of Statistics
(2022)
50,
324
(DOI: 10.1214/21-aos2107)
High‐dimensional, multiscale online changepoint detection
– Journal of the Royal Statistical Society. Series B: Statistical Methodology
(2022)
84,
234
(DOI: 10.1111/rssb.12447)
High‐dimensional, multiscale online changepoint detection
– Journal of the Royal Statistical Society: Series B (Statistical Methodology)
(2022)
84,
234
(DOI: 10.1111/rssb.12447)
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