Richard Nickl | Academic Influence

Richard Nickl's AcademicInfluence.com Rankings

Richard Nickl

Mathematics

#3917

World Rank

#5663

Historical Rank

Probability Theory

#163

World Rank

#193

Historical Rank

Statistics

#593

World Rank

#674

Historical Rank

Measure Theory

#4127

World Rank

#4865

Historical Rank

mathematics Degrees

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Mathematics

Richard Nickl's Degrees

PhD Mathematics University of Vienna
Masters Mathematics University of Vienna
Bachelors Mathematics University of Vienna

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Why Is Richard Nickl Influential?

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According to Wikipedia, Richard Nickl is an Austrian mathematician and Professor of Mathematical Statistics at the University of Cambridge. He is a fellow of Gonville and Caius College. He grew up in Vienna, attended secondary school at the Theresianum there and obtained his academic degrees from the University of Vienna, including a PhD in 2005. He has made contributions to various areas of mathematical statistics; including non-parametric and high-dimensional statistics, empirical process theory, and Bayesian inference for statistical inverse problems and partial differential equations. Jointly with Evarist Giné, he is the author of the book `Mathematical foundations of infinite-dimensional statistical models', published with Cambridge University Press, which won the 2017 PROSE Award for best monograph in the mathematics category. He was an invited speaker at the 2022 International Congress of Mathematicians and at the 8th European Congress of Mathematics . He has been awarded the 2017 Ethel Newbold Prize of the Bernoulli Society as well as a Consolidator Grant and an Advanced Grant by the European Research Council.

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Richard Nickl's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Mathematical Foundations of Infinite-Dimensional Statistical Models (2015) (512)
CONFIDENCE BANDS IN DENSITY ESTIMATION (2010) (168)
Nonparametric Bernstein–von Mises theorems in Gaussian white noise (2012) (134)
On the Bernstein–von Mises phenomenon for nonparametric Bayes procedures (2013) (120)
Confidence sets in sparse regression (2012) (103)
Rates of contraction for posterior distributions in Lr-metrics, 1 ≤ r ≤ ∞ (2011) (102)
Bracketing Metric Entropy Rates and Empirical Central Limit Theorems for Function Classes of Besov- and Sobolev-Type (2007) (93)
A Donsker Theorem for Lévy Measures (2012) (88)
GLOBAL UNIFORM RISK BOUNDS FOR WAVELET DECONVOLUTION ESTIMATORS (2011) (87)
On adaptive inference and confidence bands (2011) (80)
Uniform central limit theorems for kernel density estimators (2008) (76)
Uniform limit theorems for wavelet density estimators (2008) (74)
Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions (2015) (71)
An exponential inequality for the distribution function of the kernel density estimator, with applications to adaptive estimation (2009) (68)
A simple adaptive estimator of the integrated square of a density (2008) (57)
Bernstein–von Mises theorems for statistical inverse problems I: Schrödinger equation (2017) (51)
Adaptive confidence sets in $$L^2$$ (2011) (46)
Efficient nonparametric Bayesian inference for $X$-ray transforms (2017) (44)
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem (2019) (40)
Donsker-type theorems for nonparametric maximum likelihood estimators (2007) (38)
Consistent Inversion of Noisy Non‐Abelian X‐Ray Transforms (2019) (38)
Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions (2018) (37)
Concentration inequalities and confidence bands for needlet density estimators on compact homogeneous manifolds (2011) (36)
A sharp adaptive confidence ball for self-similar functions (2014) (34)
Bernstein–von Mises theorems for statistical inverse problems II: compound Poisson processes (2017) (31)
Convergence Rates for Penalized Least Squares Estimators in PDE Constrained Regression Problems (2018) (30)
Adaptive estimation of a distribution function and its density in sup-norm loss by wavelet and spline projections (2008) (30)
On statistical Calderón problems (2020) (29)
Efficient estimation of linear functionals of principal components (2017) (28)
High-frequency Donsker theorems for Lévy measures (2013) (25)
Spatially adaptive density estimation by localised Haar projections (2011) (23)
Adaptive confidence sets for matrix completion (2016) (20)
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems (2015) (20)
Concentration of measure (2019) (20)
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors (2020) (18)
On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms (2020) (18)
On Convergence and Convolutions of Random Signed Measures (2009) (16)
Efficient simulation-based minimum distance estimation and indirect inference (2009) (15)
ON BAYESIAN INFERENCE FOR SOME STATISTICAL INVERSE PROBLEMS WITH PARTIAL DIFFERENTIAL EQUATIONS (2017) (12)
Empirical and Gaussian processes on Besov classes (2006) (11)
On signal detection and confidence sets for low rank inference problems (2015) (10)
Inference on Covariance Operators via Concentration Inequalities: k-sample Tests, Classification, and Clustering via Rademacher Complexities (2016) (9)
On log-concave approximations of high-dimensional posterior measures and stability properties in non-linear inverse problems (2021) (9)
A Donsker Theorem for L\'evy Measures (2012) (7)
Nonparametric Bernstein-von Mises Theorems (2012) (5)
Adaptation on the space of finite signed measures (2008) (5)
Discussion of “Frequentist coverage of adaptive nonparametric Bayesian credible sets” (2014) (4)
On some information-theoretic aspects of non-linear statistical inverse problems (2021) (3)
Uniform central limit theorems for sieved maximum likelihood and trigonometric series estimators on the unit circle (2009) (2)
Donsker type theorems for nonparametric maximum likelihood estimators (2008) (2)
On statistical Calder\'on problems. (2019) (2)
Concentration inequalities and confidence bands for needlet density estimators on compact homogeneous manifolds (2011) (2)
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions (2022) (2)
Inference for diffusions from low frequency measurements (2022) (1)
Comments on: High-dimensional simultaneous inference with the bootstrap (2017) (1)
Probabilistic Techniques in Modern Statistics (2015) (1)
The mathematical work of Evarist Giné (2016) (1)
Bernoulli Adaptive confidence sets for matrix completion (2017) (0)
Likelihood-Based Procedures (2016) (0)
The Minimax Paradigm (2015) (0)
High-frequency Donsker theorems for Lévy measures (2015) (0)
Bracketing Metric Entropy Rates for Function Classes of Besov-and Sobolev-Type De ned on Borel Sets of R d (2004) (0)
Nonparametric Statistical Models (2015) (0)
On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions (2022) (0)
Linear Nonparametric Estimators (2021) (0)
Foundations of Bayesian Inference for Complex Statistical Models (2022) (0)
The mathematical work of Evarist Giné. (Catalan) (2017) (0)
CONFIDENCE BANDS IN DENSITY ESTIMATION BY EVARIST GINÉ (2010) (0)
English summaries (1989) (0)
Function Spaces and Approximation Theory (2016) (0)
A Conversation with Dick Dudley (2019) (0)
Comments on: High-dimensional simultaneous inference with the bootstrap (2017) (0)
In Memoriam: Evarist Giné (2016) (0)

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