Journal of Computational and Graphical Statistics

Article	Citations
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods	67
Efficient Estimation of Parameters in Marginals in Semiparametric Multivariate Models	52
Distance-based Clustering of Functional Data with Derivative Principal Component Analysis	41
Functional Nonlinear Learning	40
Joint Modeling of Longitudinal Imaging and Survival Data	31
A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance	29
Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization	24
Generalized Tensor Decomposition With Features on Multiple Modes	23
Analytic Permutation Testing for Functional Data ANOVA	22
Double Probability Integral Transform Residuals for Regression Models with Discrete Outcomes	21
Simultaneous estimation of connectivity and dimensionality in samples of networks	20
Local Clustering for Functional Data	18
Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach	16
Implicit Copula Variational Inference	16
Fast Conservative Monte Carlo Confidence Sets	15
Integrated Depths for Partially Observed Functional Data	15
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	14
Gibbs Sampling for Mixtures in Order of Appearance: The Ordered Allocation Sampler	14
Graphical Influence Diagnostics for Changepoint Models	14
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference	13
Structured Shrinkage Priors	13
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory	13
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers	13
Biconvex Clustering	13
Dynamic Prediction Using Landmark Historical Functional Cox Regression	12

Bayesian Computation in Dynamic Latent Factor Models	12
Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models	12
Functional Mixed Membership Models	12
Functional Projection K -means	12
Using Rejection Sampling Probability of Acceptance as a Measure of Independence	12
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference	12
Non-Conjugate Variational Bayes for Pseudo-Likelihood Mixed Effect Models	12
Tree-Enhanced Latent Space Models for Two-Mode Networks	12
Enforcing Stationarity through the Prior in Vector Autoregressions	11
Bayesian Adaptive Tucker Decompositions for Tensor Factorization	11
Optimal Integrating Learning for Split Questionnaire Design Type Data	11
Backward Importance Sampling for Online Estimation of State Space Models	11
On Inference for Modularity Statistics in Structured Networks	10
Computationally Efficient Learning of Gaussian Linear Structural Equation Models with Equal Error Variances	10
An Extension of the Unified Skew-Normal Family of Distributions and its Application to Bayesian Binary Regression	10
Massive Parallelization of Massive Sample-Size Survival Analysis	10
Convergence of Position-Dependent MALA with Application to Conditional Simulation in GLMMs	9
Inference and Computation for Sparsely Sampled Random Surfaces	9
Bayesian Nowcasting with Laplacian-P-Splines	9
Gaussian Variational Approximation for Ordinal Data with Crossed Random Effects	9
EM Algorithm for the Estimation of the RETAS Model	8
Scalable Feature Matching Across Large Data Collections	8
Ultra-Efficient MCMC for Bayesian Longitudinal Functional Data Analysis	8
Fast Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models	8
On Data Augmentation for Models Involving Reciprocal Gamma Functions	8
Multi-label Random Subspace Ensemble Classification	8
On the Use of Minimum Penalties in Statistical Learning	8
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	8
Scalable Estimation and Two-Sample Testing for Large Networks via Subsampling	8
Search Algorithms and Loss Functions for Bayesian Clustering	7
Competing Risk Modeling with Bivariate Varying Coefficients to Understand the Dynamic Impact of COVID-19	7
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	7
Measure of Strength of Evidence for Visually Observed Differences between Subpopulations	7
A Projection Approach to Local Regression with Variable-Dimension Covariates	7
Correction	7
Wavelet Feature Screening	7
Learning Subspaces of Different Dimensions	7
Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions	6
A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters	6
Variational Bayes in State Space Models: Inferential and Predictive Accuracy	6
Multivariate Moment Least-Squares Variance Estimators for Reversible Markov Chains	6
Model Checking for Logistic Models When the Number of Parameters Tends to Infinity	6
Adaptive Semiparametric Bayesian Differential Equations Via Sequential Monte Carlo	6
Bayesian Distance Weighted Discrimination	6
A Flexible Framework for Synthesizing Categorical Sequences with Application to Human Activity Patterns	6
Can You See The Change? Change Point Detection Using Visual Inference	6
Meta Clustering for Collaborative Learning	6
More Powerful Selective Inference for the Graph Fused Lasso	6
Double-Matched Matrix Decomposition for Multi-View Data	6
Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model	6

Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	6
Bootstrap Inference for Linear Time-Varying Coefficient Models in Locally Stationary Time Series	6
On Exact Computation of Tukey Depth Central Regions	6
Vecchia Likelihood Approximation for Accurate and Fast Inference with Intractable Spatial Max-Stable Models	6
Fluid Correlation: A Novel Nonparametric Metric to Assess the Dynamic Association	5
Dependence Model Assessment and Selection with DecoupleNets	5
FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions	5
Deeply Learned Generalized Linear Models with Missing Data	5
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates	5
Monotone Cubic B-Splines with a Neural-Network Generator	5
An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression	5
DeepMoM: Robust Deep Learning With Median-of-Means	5
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects	5
Supervised Principal Component Regression for Functional Responses with High Dimensional Predictors	5
Scalable Inference for Hybrid Bayesian Hidden Markov Model Using Gaussian Process Emission	5
A Fast Solution to the Lasso Problem with Equality Constraints	5
Approximate Bayesian Computation with Deep Learning and Conformal prediction	5
Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models	5
Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity	5
A Generalized Quantile Tree Method for Subgroup Identification	5
Spatial Heterogeneous Additive Partial Linear Model: A Joint Approach of Bivariate Spline and Forest Lasso	5
Accelerated Structured Matrix Factorization	5
A Probit Tensor Factorization Model For Relational Learning	5
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data	5
Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction	5
AddiVortes: (Bayesian) Additive Voronoi Tessellations	5
Deep Neural Network for Functional Graphical Models Structure Learning	5
The Mean Shape under the Relative Curvature Condition	5
Nonlinear Functional Modeling Using Neural Networks	5
Dependent Modeling of Temporal Sequences of Random Partitions	5
On the Wasserstein Median of Probability Measures	4
Group-Orthogonal Subsampling for Hierarchical Data Based on Linear Mixed Models	4
Heterogeneous Functional Regression for Subgroup Analysis	4
Generative Quantile Regression with Variability Penalty	4
Co-Factor Analysis of Citation Networks	4
Triangular Concordance Learning of Networks	4
Communication-Efficient Nonparametric Quantile Regression via Random Features	4
A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices	4
Semiparametric Weighted Spline Regression (SWSR) in Confirmatory Clinical Trials with Time-Varying Placebo Effects	4
Simultaneous Estimation of Multiple Treatment Effects from Observational Studies	4
A Multi-Attribute Evaluation of Genotype-Environment Experiments Using Biplots and Joint Plots Graphics	4
Structured Variational Approximations with Skew Normal Decomposable Graphical Models and Implicit Copulas	4
Principal Variables Analysis for Non-Gaussian Data	4
Efficient Modeling of Spatial Extremes over Large Geographical Domains	4
On Seeded Subgraph-to-Subgraph Matching: The ssSGM Algorithm and Matchability Information Theory	4
Approximating Partial Likelihood Estimators via Optimal Subsampling	4
Varying Coefficient Model via Adaptive Spline Fitting	4
Nonstationary Spatial Modeling of Massive Global Satellite Data	4
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	4
Community Detection with Heterogeneous Block Covariance Model	4
On Construction and Estimation of Stationary Mixture Transition Distribution Models	4
Big Data Model Building Using Dimension Reduction and Sample Selection	4
Distributed Learning for Principal Eigenspaces without Moment Constraints	4
Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model	4
Data Integration with Oracle Use of External Information from Heterogeneous Populations	4
Eye Fitting Straight Lines in the Modern Era	4
A Cepstral Model for Efficient Spectral Analysis of Covariate-Dependent Time Series	4
Asynchronous and Distributed Data Augmentation for Massive Data Settings	4
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	4
Hybrid Kronecker Product Decomposition and Approximation	4
AutoGFI: Streamlined Generalized Fiducial Inference for Modern Inference Problems in Models with Additive Errors	4
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Modeling Longitudinal Data Using Matrix Completion	3
Predictive Subdata Selection for Computer Models	3
A Reproducing Kernel Hilbert Space Framework for Functional Classification	3
No More, No Less than Sum of Its Parts: Groups, Monoids, and the Algebra of Graphics, Statistics, and Interaction	3
Generative Filtering for Recursive Bayesian Inference with Streaming Data	3
The Journal of Computational and Graphical Statistics 2023 Associate Editors	3
Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition	3
Efficient Approximation of Leverage Scores in Two-Dimensional Autoregressive Models with Application to Image Anomaly Detection	3
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	3
Fast Computer Model Calibration using Annealed and Transformed Variational Inference	3
Online Kernel-Based Mode Learning	3
Metaheuristic Solutions to Order-of-Addition Design Problems	3
Improved Estimation of High-dimensional Additive Models Using Subspace Learning	3
Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm	3
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	3
Variational Inference Aided Variable Selection For Spatially Structured High Dimensional Covariates	3

Adaptive Bayesian SLOPE: Model Selection With Incomplete Data	3
Fast Bayesian Record Linkage for Streaming Data Contexts	3
Boosting Prediction with Data Missing Not at Random	3
Variable Selection and Basis Learning for Ordinal Classification	3
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	3
Copulas and Histogram-Valued Data	3
Bayesian Kernel Two-Sample Testing	3
Statistical Inference in Circular Structural Model and Fitting Circles to Noisy Data	3
K-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function	3
Features of the Polynomial Biplot for Ordered Contingency Tables	3
Bayesian Multilevel Network Recovery Selection	3
A Simple Algorithm for Exact Multinomial Tests	3
Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency	3
Mixtures of Matrix-Variate Contaminated Normal Distributions	3
Loss-Based Variational Bayes Prediction	3
Eigen-Adjusted Functional Principal Component Analysis	3
A Stability Framework for Parameter Selection in the Minimum Covariance Determinant Problem	3
Differentially Private Methods for Compositional Data	2
Powerful Significance Testing for Unbalanced Clusters	2
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	2
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods	2
A Distribution-Free Method for Change Point Detection in Non-Sparse High Dimensional Data	2
Finite Mixtures of Multivariate Contaminated Normal Censored Regression Models	2
Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks	2
Bayesian estimation of clustered dependence structures in functional neuroconnectivity	2
Random Forest Adjustment for Approximate Bayesian Computation	2
Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models	2
Supervised Stratified Subsampling for Predictive Analytics	2
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	2
Fast and Robust Low-Rank Learning over Networks: A Decentralized Matrix Quantile Regression Approach	2
Log-Rank-Type Tests for Equality of Distributions in High-Dimensional Spaces	2
A Simple Divide-and-Conquer-based Distributed Method for the Accelerated Failure Time Model	2
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	2
Ultra-Fast Approximate Inference Using Variational Functional Mixed Models	2
Bayesian Heterogeneous Hidden Markov Models with an Unknown Number of States	2
Perception and Cognitive Implications of Logarithmic Scales for Exponentially Increasing Data: Perceptual Sensitivity Tested with Statistical Lineups	2
Multiple Imputation Through XGBoost	2
Efficient Large-Scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks	2
A User-Friendly Computational Framework for Robust Structured Regression with the L2 Criterion	2
A Scalable Method to Exploit Screening in Gaussian Process Models with Noise	2
Multi-Task Learning for Gaussian Graphical Regressions with High Dimensional Covariates	2
Doubly Adaptive Importance Sampling	2
Augmentation Samplers for Multinomial Probit Bayesian Additive Regression Trees	2
A Bootstrap-based Method for Testing Similarity of Matched Networks	2
Estimation and Model Selection for Nonparametric Function-on-Function Regression	2
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives	2
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference	2
Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-Like Penalty	2
Correspondence analysis on sparse bipartite graphs with hyperspecialization	2
Versatile Descent Algorithms for Group Regularization and Variable Selection in Generalized Linear Models	2
Sampling Random Graphs with Specified Degree Sequences	2
Adaptive Wavelet Domain Principal Component Analysis for Nonstationary Time Series	2
Optimization for Calibration of Survey Weights under a Large Number of Conflicting Constraints	2
Efficient Sampling From the Watson Distribution in Arbitrary Dimensions	2
Multiple Domain and Multiple Kernel Outcome-Weighted Learning for Estimating Individualized Treatment Regimes	2
Rapid Bayesian Inference for Expensive Stochastic Models	2
An Interpretable Neural Network-based Nonproportional Odds Model for Ordinal Regression	2
Joint Clustering With Alignment for Temporal Data in a One-Point-per-Experiment Setting	2
Bayesian L 1/2 Regression	2
Maximum Likelihood Estimation of Hierarchical Linear Models from Incomplete Data: Random Coefficients, Statistical Interactions, and Measurement Error	2
Exactly Uncorrelated Sparse Principal Component Analysis	2
When Tukey Meets Chauvenet: A New Boxplot Criterion for Outlier Detection	2
Functional Time Series Analysis and Visualization Based on Records	2
Smoothing Splines Approximation Using Hilbert Curve Basis Selection	2
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning	2
Generative Neural Networks for Characteristic Functions	2
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	2
Persistence Flamelets: Topological Invariants for Scale Spaces	2
smashGP: Large-Scale Spatial Modeling via Matrix-Free Gaussian Processes	2
Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models	2
Nonparametric Assessment of Variable Selection and Ranking Algorithms	2
Parameter Estimation of Binned Hawkes Processes	2
Graded Matching for Large Observational Studies	2
Penguins Go Parallel: A Grammar of Graphics Framework for Generalized Parallel Coordinate Plots	2
Gibbs Priors for Bayesian Nonparametric Variable Selection with Weak Learners	2
Network Embedding-based Directed Community Detection with Unknown Community Number	1
Selective Imputation of Covariates in High Dimensional Censored Data	1
Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data	1
ProSpar-GP: Scalable Gaussian Process Modeling with Massive Nonstationary Datasets	1
Biplots for the Correlation Matrix	1
High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization	1
Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso	1
Sensitivity Analysis for Binary Outcome Misclassification in Randomization Tests via Integer Programming	1
Variational Inference based on a Subclass of Closed Skew Normals	1
Scalable Estimation for Structured Additive Distributional Regression	1
Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data	1
A Distributed Block-Split Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems	1
Stochastic Block Smooth Graphon Model	1
flexBART: Flexible Bayesian Regression Trees with Categorical Predictors	1
Properties of Test Statistics for Nonparametric Cointegrating Regression Functions Based on Subsamples	1
Discrete Autoregressive Switching Processes with Cumulative Shrinkage Priors for Graphical Modeling of Time Series Data	1
Interpretable Architecture Neural Networks for Function Visualization	1
Computational Methods for Fast Bayesian Model Assessment via Calibrated Posterior p -values	1
A Unified Approach to Variable Selection for Partially Linear Models	1
Generative Multi-Purpose Sampler for Weighted M-estimation	1