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Cantab Capital Institute for the Mathematics of Information

 

Professor of Mathematical Statistics

Research Interests: Mathematical Statistics; specifically high-dimensional inference, Bayesian nonparametrics, statistics for PDEs and inverse problems, empirical process theory.

 

 

Publications

Consistent Inversion of Noisy Non-Abelian X-Ray Transforms
F Monard, R Nickl, GP Paternain
(2019)
Efficient nonparametric Bayesian inference for $X$-ray transforms
F Monard, R Nickl, GP Paternain
– Annals of Statistics
(2019)
47,
1113
A Conversation with Dick Dudley
V Koltchinskii, R Nickl, P Rigollet
– Statistical Science
(2019)
34,
169
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
A Carpentier, J Eisert, D Gross, R Nickl
(2019)
74,
385
Bernstein-von Mises theorems for statistical inverse problems II: compound Poisson processes
R Nickl, J Söhl
– Electronic Journal of Statistics
(2019)
13,
3513
Adaptive confidence sets for matrix completion.
A Carpentier, O Klopp, M Löffler, R Nickl
– Bernoulli
(2018)
24,
2429
Inference on Covariance Operators via Concentration Inequalities: k-sample Tests, Classification, and Clustering via Rademacher Complexities
AB Kashlak, JAD Aston, R Nickl
– Sankhya A
(2018)
81A,
214
Comments on: High-dimensional simultaneous inference with the bootstrap
M Löffler, R Nickl
– Test
(2017)
26,
731
Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions
R Nickl, J Söhl
– The Annals of Statistics
(2017)
45,
1664
A sharp adaptive confidence ball for self-similar functions
R Nickl, B Szabó
– Stochastic Processes and their Applications
(2016)
126,
3913
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Research Group

Cantab Capital Institute for the Mathematics of Information

Room

D2.05

Telephone

01223 765020