OOIR: Observatory of International Research

Papers

(The TQCC of Annals of Statistics is 10. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score	330
Nonparametric regression using deep neural networks with ReLU activation function	100
Surprises in high-dimensional ridgeless least squares interpolation	75
Predictive inference with the jackknife+	72
Analytical nonlinear shrinkage of large-dimensional covariance matrices	70
Entrywise eigenvector analysis of random matrices with low expected rank	66
The hardness of conditional independence testing and the generalised covariance measure	60
E-values: Calibration, combination and applications	52
Just interpolate: Kernel “Ridgeless” regression can generalize	49
Robust inference with knockoffs	46
Robust machine learning by median-of-means: Theory and practice	45
Time-uniform, nonparametric, nonasymptotic confidence sequences	42
Learning models with uniform performance via distributionally robust optimization	41
Lasso guarantees for $\beta$-mixing heavy-tailed time series	39
Partial identifiability of restricted latent class models	34
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach	33
A simple measure of conditional dependence	31
On the rate of convergence of fully connected deep neural network regression estimates	31
Average treatment effects in the presence of unknown interference	31
Robust multivariate nonparametric tests via projection averaging	29
Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data	29
Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization	28
Limiting laws for divergent spiked eigenvalues and largest nonspiked eigenvalue of sample covariance matrices	26
A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery	25
Convergence rates of variational posterior distributions	24

Linearized two-layers neural networks in high dimension	24
Post hoc confidence bounds on false positives using reference families	24
Robust multivariate mean estimation: The optimality of trimmed mean	24
A general approach for cure models in survival analysis	23
Foundations of structural causal models with cycles and latent variables	23
Transfer learning for nonparametric classification: Minimax rate and adaptive classifier	23
Approximate Message Passing algorithms for rotationally invariant matrices	22
On cross-validated Lasso in high dimensions	22
Posterior concentration for Bayesian regression trees and forests	21
High-frequency analysis of parabolic stochastic PDEs	21
Conformal prediction beyond exchangeability	20
Classification accuracy as a proxy for two-sample testing	20
Singular vector and singular subspace distribution for the matrix denoising model	20
A framework for adaptive MCMC targeting multimodal distributions	19
Permutation methods for factor analysis and PCA	19
Spiked separable covariance matrices and principal components	19
Simultaneous high-probability bounds on the false discovery proportion in structured, regression and online settings	19
Testing for stationarity of functional time series in the frequency domain	19
Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions	19
Mean estimation with sub-Gaussian rates in polynomial time	18
Distance-based and RKHS-based dependence metrics in high dimension	18
Optimal estimation of Gaussian mixtures via denoised method of moments	18
Which bridge estimator is the best for variable selection?	18
Distributed linear regression by averaging	18
Controlled sequential Monte Carlo	18
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	18
The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning	18
Nonparametric drift estimation for i.i.d. paths of stochastic differential equations	18
Estimation of low-rank matrices via approximate message passing	17
$\alpha $-variational inference with statistical guarantees	17
Concentration of tempered posteriors and of their variational approximations	17
Empirical process results for exchangeable arrays	17
Optimal change point detection and localization in sparse dynamic networks	17
Adaptive transfer learning	16
Bridging the gap between constant step size stochastic gradient descent and Markov chains	16
A general framework for Bayes structured linear models	16
Isotropic covariance functions on graphs and their edges	16
Nonasymptotic upper bounds for the reconstruction error of PCA	16
Only closed testing procedures are admissible for controlling false discovery proportions	16
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising	16
Local uncertainty sampling for large-scale multiclass logistic regression	16
Optimal rates of entropy estimation over Lipschitz balls	16
Optimality of spectral clustering in the Gaussian mixture model	16
The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy	15
Asymptotically independent U-statistics in high-dimensional testing	15
Minimax rates in sparse, high-dimensional change point detection	15
Geometrizing rates of convergence under local differential privacy constraints	15
Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors	15
Relaxing the assumptions of knockoffs by conditioning	15
Functional data analysis in the Banach space of continuous functions	14

Construction of mixed orthogonal arrays with high strength	14
High-dimensional consistent independence testing with maxima of rank correlations	14
On the optimal reconstruction of partially observed functional data	14
Testing in high-dimensional spiked models	13
Factor-driven two-regime regression	13
Segmentation and estimation of change-point models: False positive control and confidence regions	13
Bridging convex and nonconvex optimization in robust PCA: Noise, outliers and missing data	13
Large sample properties of partitioning-based series estimators	13
Test of significance for high-dimensional longitudinal data	13
Valid post-selection inference in model-free linear regression	13
Asymptotic distributions of high-dimensional distance correlation inference	13
Conditional calibration for false discovery rate control under dependence	13
Theoretical and computational guarantees of mean field variational inference for community detection	12
Causal discovery in heavy-tailed models	12
Two-sample hypothesis testing for inhomogeneous random graphs	12
Subspace estimation from unbalanced and incomplete data matrices: ℓ2,∞ statistical guarantees	12
Statistically optimal and computationally efficient low rank tensor completion from noisy entries	12
On estimation of isotonic piecewise constant signals	12
Fréchet change-point detection	12
Additive regression with Hilbertian responses	12
Rejoinder: “Nonparametric regression using deep neural networks with ReLU activation function”	12
Augmented minimax linear estimation	12
Testing for outliers with conformal p-values	12
Distribution and correlation-free two-sample test of high-dimensional means	11
Community detection on mixture multilayer networks via regularized tensor decomposition	11
Heteroskedastic PCA: Algorithm, optimality, and applications	11
Hypothesis testing for high-dimensional time series via self-normalization	11
Adaptive test of independence based on HSIC measures	11
Coupled conditional backward sampling particle filter	11
Bootstrapping max statistics in high dimensions: Near-parametric rates under weak variance decay and application to functional and multinomial data	11
Optimal adaptivity of signed-polygon statistics for network testing	11
Semiparametric optimal estimation with nonignorable nonresponse data	11
Fundamental limits of detection in the spiked Wigner model	11
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	11
Robust covariance estimation under $L_{4}-L_{2}$ norm equivalence	11
Joint estimation of parameters in Ising model	11
Testing community structure for hypergraphs	11
Inference for change points in high-dimensional data via selfnormalization	11
Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario	11
On spike and slab empirical Bayes multiple testing	11
An optimal statistical and computational framework for generalized tensor estimation	11
Learning a tree-structured Ising model in order to make predictions	11
Robust inference via multiplier bootstrap	10
Density deconvolution under general assumptions on the distribution of measurement errors	10
Estimation of the number of components of nonparametric multivariate finite mixture models	10
LASSO-driven inference in time and space	10
Monitoring for a change point in a sequence of distributions	10
Random graph asymptotics for treatment effect estimation under network interference	10
Local nearest neighbour classification with applications to semi-supervised learning	10
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	10
Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes	10
Singularity, misspecification and the convergence rate of EM	10
Minimax optimal rates for Mondrian trees and forests	10
Distributed statistical inference for massive data	10
Extending the validity of frequency domain bootstrap methods to general stationary processes	10
Empirical Bayes oracle uncertainty quantification for regression	10
Minimax optimal conditional independence testing	10
Semiparametric Bayesian causal inference	10
An adaptable generalization of Hotelling’s $T^{2}$ test in high dimension	10