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Department of Pure Mathematics and Mathematical Statistics

 

Professor of Mathematical Statistics

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

 

 

Publications

On statistical Calderón problems
K Abraham, R Nickl
– Mathematical Statistics and Learning
(2020)
2,
165
Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions
R Nickl, K Ray
– The Annals of Statistics
(2020)
48,
1383
Bernstein-von Mises theorems for statistical inverse problems I: Schrodinger equation
R Nickl
– Journal of the European Mathematical Society
(2020)
22,
2697
Convergence rates for penalized least squares estimators in PDE constrained regression problems
R Nickl, S Van De Geer, S Wang
– SIAM/ASA Journal on Uncertainty Quantification
(2020)
8,
374
Efficient estimation of linear functionals of principal components
V Koltchinskii, M Loffler, R Nickl
– The Annals of Statistics
(2020)
48,
464
Efficient estimation of linear functionals of principal components
V Koltchinskii, M Löffler, R Nickl
– Annals of Statistics
(2020)
48,
464
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
A Carpentier, J Eisert, D Gross, R Nickl
– pp
(2019)
3,
385
On statistical Calderón problems
K Abraham, R Nickl
(2019)
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
– The Annals of Statistics
(2019)
47,
1113
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Room

D2.05

Telephone

01223 765020