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 2020-05-01 to 2024-05-01.)

Article	Citations
Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance	61
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes	33
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
Ensemble slice sampling	16
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
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
Analysis of stochastic gradient descent in continuous time	12
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison	12
Unbiased estimation of the gradient of the log-likelihood in inverse problems	11
Implicitly adaptive importance sampling	11
Convergence rates for optimised adaptive importance samplers	11
Composite likelihood methods for histogram-valued random variables	10
On the performance of particle filters with adaptive number of particles	10
A piecewise deterministic Monte Carlo method for diffusion bridges	10
Bayesian additive regression trees with model trees	10
Constrained parsimonious model-based clustering	10
Bayesian ODE solvers: the maximum a posteriori estimate	10
Properties of the stochastic approximation EM algorithm with mini-batch sampling	9
A wavelet-based approach for imputation in nonstationary multivariate time series	9
Multilevel particle filters for the non-linear filtering problem in continuous time	9
Convergence rates of Gaussian ODE filters	9

Parallelized integrated nested Laplace approximations for fast Bayesian inference	9
Cauchy Markov random field priors for Bayesian inversion	9
Locally induced Gaussian processes for large-scale simulation experiments	9
Consistent online Gaussian process regression without the sample complexity bottleneck	8
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming	8
Bayesian estimation of the latent dimension and communities in stochastic blockmodels	8
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks	8
Accelerating sequential Monte Carlo with surrogate likelihoods	8
Fisher Scoring for crossed factor linear mixed models	8
Point process simulation of generalised inverse Gaussian processes and estimation of the Jaeger integral	7
Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data	7
Simulating space-time random fields with nonseparable Gneiting-type covariance functions	7
Deep state-space Gaussian processes	7
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers	7
Stochastic approximation cut algorithm for inference in modularized Bayesian models	7
Regularized bi-directional co-clustering	7
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport	7
On the identifiability of Bayesian factor analytic models	7
A comparison of likelihood-free methods with and without summary statistics	7
Outlier detection in non-elliptical data by kernel MRCD	7
Proximal nested sampling for high-dimensional Bayesian model selection	7
Efficient importance sampling for large sums of independent and identically distributed random variables	7
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo	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
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics	6
The recursive variational Gaussian approximation (R-VGA)	6
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence	6
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo	6
Sequential Bayesian optimal experimental design for structural reliability analysis	6
Bayesian inference for continuous-time hidden Markov models with an unknown number of states	6
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering	6
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion	6
Automatic Zig-Zag sampling in practice	6
A closed-form filter for binary time series	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
Particle-based energetic variational inference	5
Changepoint detection in non-exchangeable data	5
A robust and efficient algorithm to find profile likelihood confidence intervals	5
Generalised joint regression for count data: a penalty extension for competitive settings	5
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter	5
Markov chain Monte Carlo algorithms with sequential proposals	5
Variational Bayes on manifolds	5
An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models	5
Fitting Matérn smoothness parameters using automatic differentiation	5
Wavelet-based robust estimation and variable selection in nonparametric additive models	5
Variable selection using a smooth information criterion for distributional regression models	5
Model-based clustering with determinant-and-shape constraint	5
Robust fitting for generalized additive models for location, scale and shape	5
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy	4

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation	4
Rank-one multi-reference factor analysis	4
Bayesian numerical methods for nonlinear partial differential equations	4
Generalized parallel tempering on Bayesian inverse problems	4
Quantile hidden semi-Markov models for multivariate time series	4
On automatic bias reduction for extreme expectile estimation	4
Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters	4
Improved inference for areal unit count data using graph-based optimisation	4
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi’s pseudodistance estimators	4
An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests	4
Adaptation of the tuning parameter in general Bayesian inference with robust divergence	4
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling	4
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance	4
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation	4
Multi-scale process modelling and distributed computation for spatial data	4
Product-form estimators: exploiting independence to scale up Monte Carlo	4
Sklar’s Omega: A Gaussian copula-based framework for assessing agreement	4
Systematic enumeration of definitive screening designs	4
BayesProject: Fast computation of a projection direction for multivariate changepoint detection	4
A simple method for rejection sampling efficiency improvement on SIMT architectures	3
Uncertainty modelling and computational aspects of data association	3
Efficient EM-variational inference for nonparametric Hawkes process	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
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization	3
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities	3
Graph matching beyond perfectly-overlapping Erdős–Rényi random graphs	3
Parallelizing MCMC sampling via space partitioning	3
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference	3
Subsampling sequential Monte Carlo for static Bayesian models	3
Variable selection using conditional AIC for linear mixed models with data-driven transformations	3
On some consistent tests of mutual independence among several random vectors of arbitrary dimensions	3
Deep mixtures of unigrams for uncovering topics in textual data	3
A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions	3
Sparse functional partial least squares regression with a locally sparse slope function	3
Model-free global likelihood subsampling for massive data	3
Maximum likelihood estimation of the Fisher–Bingham distribution via efficient calculation of its normalizing constant	3
A random persistence diagram generator	3
Optimal representative sample weighting	3
Importance conditional sampling for Pitman–Yor mixtures	3
Robust discrete choice models with t-distributed kernel errors	3
A SUR version of the Bichon criterion for excursion set estimation	3
Constructing two-level $$Q_B$$-optimal screening designs using mixed-integer programming and heuristic algorithms	3
High-dimensional order-free multivariate spatial disease mapping	3
Control variate selection for Monte Carlo integration	3
Sampling hierarchies of discrete random structures	3