Statistics and Computing

Article	Citations
Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance	79
Ensemble slice sampling	24
Ensemble Kalman inversion: mean-field limit and convergence analysis	23
Gaussian process learning via Fisher scoring of Vecchia’s approximation	21
Implicitly adaptive importance sampling	17
Bayesian additive regression trees with model trees	16
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison	15
Analysis of stochastic gradient descent in continuous time	14
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes	14
On the performance of particle filters with adaptive number of particles	13
GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model	13
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming	13
Proximal nested sampling for high-dimensional Bayesian model selection	13
A wavelet-based approach for imputation in nonstationary multivariate time series	12
A piecewise deterministic Monte Carlo method for diffusion bridges	11
On the identifiability of Bayesian factor analytic models	11
Convergence rates for optimised adaptive importance samplers	11
Parallelized integrated nested Laplace approximations for fast Bayesian inference	11
Constrained parsimonious model-based clustering	10
Bayesian ODE solvers: the maximum a posteriori estimate	10
Cauchy Markov random field priors for Bayesian inversion	10
Fisher Scoring for crossed factor linear mixed models	10
Unbiased estimation of the gradient of the log-likelihood in inverse problems	10
Locally induced Gaussian processes for large-scale simulation experiments	10
Regularized bi-directional co-clustering	9

Accelerating sequential Monte Carlo with surrogate likelihoods	8
A closed-form filter for binary time series	8
Variational Bayes on manifolds	8
Outlier detection in non-elliptical data by kernel MRCD	8
Sequential Bayesian optimal experimental design for structural reliability analysis	8
Stochastic approximation cut algorithm for inference in modularized Bayesian models	8
Modern non-linear function-on-function regression	8
Consistent online Gaussian process regression without the sample complexity bottleneck	8
Deep state-space Gaussian processes	7
Efficient importance sampling for large sums of independent and identically distributed random variables	7
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers	7
A comparison of likelihood-free methods with and without summary statistics	7
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion	7
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo	7
Variable selection using a smooth information criterion for distributional regression models	7
The recursive variational Gaussian approximation (R-VGA)	7
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering	7
Bayesian numerical methods for nonlinear partial differential equations	7
Automatic Zig-Zag sampling in practice	7
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport	7
On automatic bias reduction for extreme expectile estimation	7
Robust fitting for generalized additive models for location, scale and shape	7
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo	7
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
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence	6
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling	6
A robust and efficient algorithm to find profile likelihood confidence intervals	6
Particle-based energetic variational inference	6
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics	6
Bayesian inference for continuous-time hidden Markov models with an unknown number of states	6
Fitting Matérn smoothness parameters using automatic differentiation	6
Parsimonious hidden Markov models for matrix-variate longitudinal data	6
Detecting and diagnosing prior and likelihood sensitivity with power-scaling	6
Generalized parallel tempering on Bayesian inverse problems	5
Changepoint detection in non-exchangeable data	5
Moments and random number generation for the truncated elliptical family of distributions	5
Modularized Bayesian analyses and cutting feedback in likelihood-free inference	5
An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models	5
Uncertainty modelling and computational aspects of data association	5
High-dimensional order-free multivariate spatial disease mapping	5
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities	5
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation	5
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy	5
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation	5
Random forest kernel for high-dimension low sample size classification	5
Wavelet-based robust estimation and variable selection in nonparametric additive models	5
A SUR version of the Bichon criterion for excursion set estimation	5
Adaptation of the tuning parameter in general Bayesian inference with robust divergence	5
Improved inference for areal unit count data using graph-based optimisation	5

A simple method for rejection sampling efficiency improvement on SIMT architectures	5
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi’s pseudodistance estimators	5
The forward–backward envelope for sampling with the overdamped Langevin algorithm	4
Statistical depth in abstract metric spaces	4
Deep mixtures of unigrams for uncovering topics in textual data	4
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization	4
Systematic enumeration of definitive screening designs	4
Multilevel estimation of normalization constants using ensemble Kalman–Bucy filters	4
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models	4
Achieving fairness with a simple ridge penalty	4
An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests	4
Sparse functional partial least squares regression with a locally sparse slope function	4
Model-free global likelihood subsampling for massive data	4
A random persistence diagram generator	4
Rank-one multi-reference factor analysis	4
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity	4
Sklar’s Omega: A Gaussian copula-based framework for assessing agreement	4
Product-form estimators: exploiting independence to scale up Monte Carlo	4
Quantile hidden semi-Markov models for multivariate time series	4
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance	4
Optimal representative sample weighting	4
Control variate selection for Monte Carlo integration	3
Parallelizing MCMC sampling via space partitioning	3
Split Hamiltonian Monte Carlo revisited	3
Variable selection and regularization via arbitrary rectangle-range generalized elastic net	3
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems	3
Importance conditional sampling for Pitman–Yor mixtures	3
Efficient EM-variational inference for nonparametric Hawkes process	3
Distributional anchor regression	3
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection	3
Efficient probabilistic reconciliation of forecasts for real-valued and count time series	3
Generating directed networks with predetermined assortativity measures	3
Constructing two-level $$Q_B$$-optimal screening designs using mixed-integer programming and heuristic algorithms	3
Graph matching beyond perfectly-overlapping Erdős–Rényi random graphs	3
Maximum likelihood estimation of the Fisher–Bingham distribution via efficient calculation of its normalizing constant	3
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions	3
Efficient and accurate inference for mixtures of Mallows models with Spearman distance	3
Consistent causal inference from time series with PC algorithm and its time-aware extension	3
Limitations of the Wasserstein MDE for univariate data	3
LASSO for streaming data with adaptative filtering	3
On estimating the structure factor of a point process, with applications to hyperuniformity	3
Variable selection using conditional AIC for linear mixed models with data-driven transformations	3
Robust discrete choice models with t-distributed kernel errors	3
Penalized Cox’s proportional hazards model for high-dimensional survival data with grouped predictors	3
Bayesian projection pursuit regression	3
A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions	3
Generalised likelihood profiles for models with intractable likelihoods	3
Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference	3
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics	3
Distributed statistical optimization for non-randomly stored big data with application to penalized learning	3
Flexible non-parametric regression models for compositional response data with zeros	3
Min–max crossover designs for two treatments binary and poisson crossover trials	3
Bayesian variable selection for matrix autoregressive models	3
Model averaging for support vector classifier by cross-validation	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
Accelerating the estimation of renewal Hawkes self-exciting point processes	3
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems	3
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization	2
Sequential sampling of junction trees for decomposable graphs	2
Bayesian wavelet-packet historical functional linear models	2
Quantile regression feature selection and estimation with grouped variables using Huber approximation	2
Fast Bayesian inversion for high dimensional inverse problems	2
Toeplitz Monte Carlo	2
A Bayesian parametrized method for interval-valued regression models	2
Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods	2
Selecting the derivative of a functional covariate in scalar-on-function regression	2
Comparing unconstrained parametrization methods for return covariance matrix prediction	2
Non-local spatially varying finite mixture models for image segmentation	2
Cauchy robust principal component analysis with applications to high-dimensional data sets	2
De-noising boosting methods for variable selection and estimation subject to error-prone variables	2
Conditional particle filters with diffuse initial distributions	2
Quantifying uncertainty with a derivative tracking SDE model and application to wind power forecast data	2
Variational Tobit Gaussian Process Regression	2
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm	2
Rate-optimal refinement strategies for local approximation MCMC	2
GParareal: a time-parallel ODE solver using Gaussian process emulation	2
Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data	2
Nonnegative Bayesian nonparametric factor models with completely random measures	2
Point process simulation of generalised hyperbolic Lévy processes	2
Stochastic cluster embedding	2

Automatic search intervals for the smoothing parameter in penalized splines	2
Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models	2
Efficient and generalizable tuning strategies for stochastic gradient MCMC	2
Stochastic variational inference for scalable non-stationary Gaussian process regression	2
Prediction scoring of data-driven discoveries for reproducible research	2
A fast epigraph and hypograph-based approach for clustering functional data	2
Power-law distribution in pieces: a semi-parametric approach with change point detection	2
A framework for mediation analysis with massive data	2
Complexity of zigzag sampling algorithm for strongly log-concave distributions	2
Testing symmetry for bivariate copulas using Bernstein polynomials	2
Truncated Poisson–Dirichlet approximation for Dirichlet process hierarchical models	2
Multiscale stick-breaking mixture models	2
A branch-and-bound algorithm for the exact optimal experimental design problem	2
Modal Clustering Using Semiparametric Mixtures and Mode Flattening	2
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference	2
NuZZ: Numerical Zig-Zag for general models	2
Bayesian learning via neural Schrödinger–Föllmer flows	2
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models	2
Eigenfunction martingale estimating functions and filtered data for drift estimation of discretely observed multiscale diffusions	2
A Metropolis-class sampler for targets with non-convex support	2
Penalized model-based clustering of complex functional data	2
A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes	2
A numerically stable algorithm for integrating Bayesian models using Markov melding	2
Constrained minimum energy designs	2
Ensemble sampler for infinite-dimensional inverse problems	2
Sticky PDMP samplers for sparse and local inference problems	2
Optimal design of multifactor experiments via grid exploration	2
A two-stage Bayesian semiparametric model for novelty detection with robust prior information	2
Maximum likelihood estimation of the Weibull distribution with reduced bias	2
Updating Variational Bayes: fast sequential posterior inference	2
Real time anomaly detection and categorisation	2
Identifiability and parameter estimation of the overlapped stochastic co-block model	2
Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes	2
Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach	2
Biclustering via structured regularized matrix decomposition	2
Erlang mixture modeling for Poisson process intensities	2
A robust quantile regression for bounded variables based on the Kumaraswamy Rectangular distribution	2
Fast and universal estimation of latent variable models using extended variational approximations	2
Sequential changepoint detection in neural networks with checkpoints	2
A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions	2
General Jackknife empirical likelihood and its applications	2
Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models	2
False discovery rate envelopes	2
Regularizing axis-aligned ensembles via data rotations that favor simpler learners	1
Classification of multivariate functional data on different domains with Partial Least Squares approaches	1
Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions	1
Learning-based importance sampling via stochastic optimal control for stochastic reaction networks	1
euMMD: efficiently computing the MMD two-sample test statistic for univariate data	1
Adaptive step size rules for stochastic optimization in large-scale learning	1
A framework of regularized low-rank matrix models for regression and classification	1
Efficient simulation of p-tempered $$\alpha $$-stable OU processes	1
Scalable computations for nonstationary Gaussian processes	1
A Joint estimation approach to sparse additive ordinary differential equations	1
Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-Blackwellized SMC samplers	1
Wasserstein principal component analysis for circular measures	1
Exact simulation of normal tempered stable processes of OU type with applications	1
Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data	1
An expectile computation cookbook	1
Bayesian A-optimal two-phase designs with a single blocking factor in each phase	1
The computational asymptotics of Gaussian variational inference and the Laplace approximation	1
Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms	1
Spline estimation of functional principal components via manifold conjugate gradient algorithm	1
Novel sampling method for the von Mises–Fisher distribution	1
Bayesian spatiotemporal modeling for inverse problems	1
Forward stability and model path selection	1
Functional mixtures-of-experts	1
Jittering and clustering: strategies for the construction of robust designs	1
Dynamic and robust Bayesian graphical models	1
Graph-based algorithms for phase-type distributions	1
Learning from missing data with the binary latent block model	1
A Riemannian Newton trust-region method for fitting Gaussian mixture models	1
Consistency factor for the MCD estimator at the Student-t distribution	1
Sparse logistic functional principal component analysis for binary data	1
Improving bridge estimators via f-GAN	1
Confidence graphs for graphical model selection	1
Variable selection using axis-aligned random projections for partial least-squares regression	1
Robust score matching for compositional data	1
A fast and calibrated computer model emulator: an empirical Bayes approach	1
Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities	1
MALA with annealed proposals: a generalization of locally and globally balanced proposal distributions	1
Functional concurrent hidden Markov model	1
Particle gradient descent model for point process generation	1
Comprehensive study of variational Bayes classification for dense deep neural networks	1
Accelerated gradient methods for sparse statistical learning with nonconvex penalties	1
Variance reduction for additive functionals of Markov chains via martingale representations	1
Joint latent space models for ranking data and social network	1
Uncertainty calibration for probabilistic projection methods	1
A 4D-Var method with flow-dependent background covariances for the shallow-water equations	1
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration	1
Adaptive online variance estimation in particle filters: the ALVar estimator	1
A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance	1
State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables	1
Interpolating log-determinant and trace of the powers of matrix $$\textbf{A} + t\textbf{B}$$	1
Optimal experimental design for linear time invariant state–space models	1
Accelerating Bayesian inference for stochastic epidemic models using incidence data	1