OOIR: Observatory of International Research

Papers

(The TQCC of Annals of Statistics is 6. 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 2021-04-01 to 2025-04-01.)

Article	Citations
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	127
On singular values of data matrices with general independent columns	79
Optimal estimation and computational limit of low-rank Gaussian mixtures	66
Ridge regression revisited: Debiasing, thresholding and bootstrap	64
Change-point analysis with irregular signals	62
Online inference with multi-modal likelihood functions	61
On the approximation accuracy of Gaussian variational inference	61
Statistical inference for rough volatility: Minimax theory	59
One-step estimation of differentiable Hilbert-valued parameters	46
Online change-point detection for matrix-valued time series with latent two-way factor structure	44
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	41
Orthogonal statistical learning	33
Foundations of structural causal models with cycles and latent variables	33
Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM	31
High-dimensional nonparametric density estimation via symmetry and shape constraints	30
Inference in Ising models on dense regular graphs	27
Extreme value inference for heterogeneous power law data	27
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	27
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	27
Dispersal density estimation across scales	27
Parametric copula adjusted for non- and semiparametric regression	26
Carving model-free inference	25
Off-policy evaluation in partially observed Markov decision processes under sequential ignorability	24
The Stein effect for Fréchet means	24
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	24

Principal components in linear mixed models with general bulk	24
Scalable estimation and inference for censored quantile regression process	24
MARS via LASSO	22
On the disjoint and sliding block maxima method for piecewise stationary time series	21
Adaptive estimation in multivariate response regression with hidden variables	21
Locally simultaneous inference	21
Metric statistics: Exploration and inference for random objects with distance profiles	21
Robust k-means clustering for distributions with two moments	21
The adaptive Wynn algorithm in generalized linear models with univariate response	20
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	20
Large-scale inference with block structure	19
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	19
Optimization hierarchy for fair statistical decision problems	19
Optimal disclosure risk assessment	19
Half-trek criterion for identifiability of latent variable models	18
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators	17
Choosing between persistent and stationary volatility	17
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	17
Variable selection consistency of Gaussian process regression	16
Convergence rates of oblique regression trees for flexible function libraries	16
On universally consistent and fully distribution-free rank tests of vector independence	16
Boosted nonparametric hazards with time-dependent covariates	16
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	16
On the sample complexity of entropic optimal transport	15
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	15
Nonlinear global Fréchet regression for random objects via weak conditional expectation	15
Empirical partially Bayes multiple testing and compound χ2 decisions	15
Tensor clustering with planted structures: Statistical optimality and computational limits	15
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	15
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	14
On an extension of the promotion time cure model	14
Minimax optimality of permutation tests	14
Stein’s method of normal approximation: Some recollections and reflections	14
Testability of high-dimensional linear models with nonsparse structures	14
Infinite-dimensional gradient-based descent for alpha-divergence minimisation	14
Universal rank inference via residual subsampling with application to large networks	14
Adaptive robust estimation in sparse vector model	14
The completion of covariance kernels	14
Consistent nonparametric estimation for heavy-tailed sparse graphs	13
Marginal singularity and the benefits of labels in covariate-shift	13
Nonparametric Bayesian inference for reversible multidimensional diffusions	13
Sharp global convergence guarantees for iterative nonconvex optimization with random data	12
Learning models with uniform performance via distributionally robust optimization	12
Gaussian approximation for nonstationary time series with optimal rate and explicit construction	12
Deep learning for the partially linear Cox model	12
A Gaussian process approach to model checks	12
A conformal test of linear models via permutation-augmented regressions	12
An optimal statistical and computational framework for generalized tensor estimation	12
Efficiency in local differential privacy	12
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach	11

Bridging factor and sparse models	11
E-values: Calibration, combination and applications	11
Semiparametric latent-class models for multivariate longitudinal and survival data	11
Conformal prediction beyond exchangeability	11
AutoRegressive approximations to nonstationary time series with inference and applications	11
Average treatment effects in the presence of unknown interference	11
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	11
Editorial: Memorial issue for Charles Stein	10
Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation	10
The projected covariance measure for assumption-lean variable significance testing	10
Factor-driven two-regime regression	10
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility	10
Nonparametric conditional local independence testing	10
Volatility coupling	10
Rate-optimal cluster-randomized designs for spatial interference	10
Correction note: “Asymptotic spectral theory for nonlinear time series”	10
On fixed-domain asymptotics, parameter estimation and isotropic Gaussian random fields with Matérn covariance functions	9
Adaptive and robust multi-task learning	9
Cube root weak convergence of empirical estimators of a density level set	9
Adaptive estimation of multivariate piecewise polynomials and bounded variation functions by optimal decision trees	9
Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model	9
Charles Stein and invariance: Beginning with the Hunt–Stein theorem	9
Settling the sample complexity of model-based offline reinforcement learning	8
Analysis of “learn-as-you-go” (LAGO) studies	8
An asymptotic test for constancy of the variance under short-range dependence	8
What is resolution? A statistical minimax testing perspective on superresolution microscopy	8
Density deconvolution under general assumptions on the distribution of measurement errors	8
Statistical inference for decentralized federated learning	8
A general characterization of optimal tie-breaker designs	8
Graphical models for nonstationary time series	8
Estimation of mixed fractional stable processes using high-frequency data	8
Asymptotic properties of penalized spline estimators in concave extended linear models: Rates of convergence	8
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when p/n→∞ and applications	7
Learning sparse graphons and the generalized Kesten–Stigum threshold	7
Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses	7
Early stopping for L2-boosting in high-dimensional linear models	7
Universal Bayes consistency in metric spaces	7
Inference on the maximal rank of time-varying covariance matrices using high-frequency data	7
Minimax rates for heterogeneous causal effect estimation	7
Consistent inference for diffusions from low frequency measurements	7
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	7
Optimal linear discriminators for the discrete choice model in growing dimensions	7
High-dimensional inference for dynamic treatment effects	7
Linearized two-layers neural networks in high dimension	7
SuperMix: Sparse regularization for mixtures	6
Limit theorems for distributions invariant under groups of transformations	6
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	6
Admissible ways of merging p-values under arbitrary dependence	6
Testing high-dimensional regression coefficients in linear models	6
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	6
Minimax estimation of smooth densities in Wasserstein distance	6
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	6
Existence and uniqueness of the Kronecker covariance MLE	6
Approximate and exact designs for total effects	6
Optimality of spectral clustering in the Gaussian mixture model	6
Statistical inference for principal components of spiked covariance matrices	6
Improved central limit theorem and bootstrap approximations in high dimensions	6
Integrative methods for post-selection inference under convex constraints	6
How do noise tails impact on deep ReLU networks?	6
Efficiency of delayed-acceptance random walk Metropolis algorithms	6
The interpolation phase transition in neural networks: Memorization and generalization under lazy training	6
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	6
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA	6
Inference for low-rank models	6
Joint sequential detection and isolation for dependent data streams	6
Adaptive test of independence based on HSIC measures	6