OOIR: Observatory of International Research

Papers

(The TQCC of Statistics and Computing is 3. 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 2020-03-01 to 2024-03-01.)

Article	Citations
Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance	59
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes	31
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach	24
Gaussian process learning via Fisher scoring of Vecchia’s approximation	18
Ensemble Kalman inversion: mean-field limit and convergence analysis	17
Imputation and low-rank estimation with Missing Not At Random data	16
High-dimensional changepoint detection via a geometrically inspired mapping	16
Ensemble slice sampling	15
Optimal non-negative forecast reconciliation	15
Anomaly and Novelty detection for robust semi-supervised learning	13
Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset	13
The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere	13
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes	13
Analysis of stochastic gradient descent in continuous time	11
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison	11
Unbiased estimation of the gradient of the log-likelihood in inverse problems	11
Inhomogeneous higher-order summary statistics for point processes on linear networks	11
Convergence rates for optimised adaptive importance samplers	10
On the performance of particle filters with adaptive number of particles	10
Composite likelihood methods for histogram-valued random variables	10
Cauchy Markov random field priors for Bayesian inversion	9
Bayesian ODE solvers: the maximum a posteriori estimate	9
A wavelet-based approach for imputation in nonstationary multivariate time series	9
Constrained parsimonious model-based clustering	9
Properties of the stochastic approximation EM algorithm with mini-batch sampling	9

A piecewise deterministic Monte Carlo method for diffusion bridges	9
Bayesian additive regression trees with model trees	9
Implicitly adaptive importance sampling	9
Convergence rates of Gaussian ODE filters	9
Likelihood-free approximate Gibbs sampling	9
Accelerating sequential Monte Carlo with surrogate likelihoods	8
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming	8
Bayesian estimation of the latent dimension and communities in stochastic blockmodels	8
Locally induced Gaussian processes for large-scale simulation experiments	8
Multilevel particle filters for the non-linear filtering problem in continuous time	8
Fisher Scoring for crossed factor linear mixed models	8
Parallelized integrated nested Laplace approximations for fast Bayesian inference	7
Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data	7
Deep state-space Gaussian processes	7
Proximal nested sampling for high-dimensional Bayesian model selection	7
Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations	7
Consistent online Gaussian process regression without the sample complexity bottleneck	7
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks	7
Outlier detection in non-elliptical data by kernel MRCD	7
Simulating space-time random fields with nonseparable Gneiting-type covariance functions	7
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence	6
GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model	6
Parsimonious hidden Markov models for matrix-variate longitudinal data	6
An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified	6
Stochastic approximation cut algorithm for inference in modularized Bayesian models	6
Automatic Zig-Zag sampling in practice	6
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport	6
High-dimensional VAR with low-rank transition	6
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo	6
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion	6
Regularized bi-directional co-clustering	6
A closed-form filter for binary time series	6
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering	6
Wavelet-based robust estimation and variable selection in nonparametric additive models	5
On the identifiability of Bayesian factor analytic models	5
Variational Bayes on manifolds	5
Robust fitting for generalized additive models for location, scale and shape	5
A comparison of likelihood-free methods with and without summary statistics	5
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo	5
Sequential Bayesian optimal experimental design for structural reliability analysis	5
Efficient importance sampling for large sums of independent and identically distributed random variables	5
A Laplace-based algorithm for Bayesian adaptive design	5
The recursive variational Gaussian approximation (R-VGA)	5
Fitting Matérn smoothness parameters using automatic differentiation	5
Particle-based energetic variational inference	5
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics	5
A robust and efficient algorithm to find profile likelihood confidence intervals	5
An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models	5
Point process simulation of generalised inverse Gaussian processes and estimation of the Jaeger integral	5
Bayesian numerical methods for nonlinear partial differential equations	4

Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter	4
Changepoint detection in non-exchangeable data	4
BayesProject: Fast computation of a projection direction for multivariate changepoint detection	4
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy	4
Generalised joint regression for count data: a penalty extension for competitive settings	4
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation	4
An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests	4
Systematic enumeration of definitive screening designs	4
Markov chain Monte Carlo algorithms with sequential proposals	4
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance	4
Improved inference for areal unit count data using graph-based optimisation	4
Conditionally structured variational Gaussian approximation with importance weights	4
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation	4
Multi-scale process modelling and distributed computation for spatial data	4
Generalized parallel tempering on Bayesian inverse problems	4
Adaptive iterative Hessian sketch via A-optimal subsampling	4
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling	4
Bayesian inference for continuous-time hidden Markov models with an unknown number of states	4
Model-based clustering with determinant-and-shape constraint	4
Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters	4
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers	4
Rank-one multi-reference factor analysis	3
A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD)	3
Robust discrete choice models with t-distributed kernel errors	3
High-dimensional order-free multivariate spatial disease mapping	3
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities	3
Model-free global likelihood subsampling for massive data	3
Control variate selection for Monte Carlo integration	3
Parallelizing MCMC sampling via space partitioning	3
Optimal representative sample weighting	3
Uncertainty modelling and computational aspects of data association	3
Bayesian nonparametric priors for hidden Markov random fields	3
Deep mixtures of unigrams for uncovering topics in textual data	3
A SUR version of the Bichon criterion for excursion set estimation	3
Quantile hidden semi-Markov models for multivariate time series	3
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference	3
On automatic bias reduction for extreme expectile estimation	3
Sampling hierarchies of discrete random structures	3
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi’s pseudodistance estimators	3
On some consistent tests of mutual independence among several random vectors of arbitrary dimensions	3
Product-form estimators: exploiting independence to scale up Monte Carlo	3
Adaptation of the tuning parameter in general Bayesian inference with robust divergence	3
Sparse functional partial least squares regression with a locally sparse slope function	3
Classification of periodic arrivals in event time data for filtering computer network traffic	3
Variable selection using a smooth information criterion for distributional regression models	3
Maximum likelihood estimation of the Fisher–Bingham distribution via efficient calculation of its normalizing constant	3
Subsampling sequential Monte Carlo for static Bayesian models	3