Journal of Computational and Graphical Statistics

Article	Citations
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods	76
Distance-based Clustering of Functional Data with Derivative Principal Component Analysis	56
Analytic Permutation Testing for Functional Data ANOVA	44
Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization	40
Efficient Estimation of Parameters in Marginals in Semiparametric Multivariate Models	31
Double Probability Integral Transform Residuals for Regression Models with Discrete Outcomes	30
Local Clustering for Functional Data	26
A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance	25
Simultaneous Estimation of Connectivity and Dimensionality in Samples of Networks	24
Joint Modeling of Longitudinal Imaging and Survival Data	24
Functional Nonlinear Learning	22
Biconvex Clustering	21
Dynamic Prediction Using Landmark Historical Functional Cox Regression	19
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference	18
Using Rejection Sampling Probability of Acceptance as a Measure of Independence	17
Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach	16
Fast Conservative Monte Carlo Confidence Sets	16
Graphical Influence Diagnostics for Changepoint Models	16
Gibbs Sampling for Mixtures in Order of Appearance: The Ordered Allocation Sampler	15
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers	15
Non-Conjugate Variational Bayes for Pseudo-Likelihood Mixed Effect Models	14
Tree-Enhanced Latent Space Models for Two-Mode Networks	14
Bayesian Computation in Dynamic Latent Factor Models	14
Functional Projection K -means	14
Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models	13

Integrated Depths for Partially Observed Functional Data	13
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory	13
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference	13
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	13
Structured Shrinkage Priors	13
Bayesian Adaptive Tucker Decompositions for Tensor Factorization	12
Implicit Copula Variational Inference	12
Backward Importance Sampling for Online Estimation of State Space Models	12
EM Algorithm for the Estimation of the RETAS Model	12
Functional Mixed Membership Models	12
Gaussian Variational Approximation for Ordinal Data with Crossed Random Effects	11
Inference and Computation for Sparsely Sampled Random Surfaces	11
Ultra-Efficient MCMC for Bayesian Longitudinal Functional Data Analysis	11
Optimal Integrating Learning for Split Questionnaire Design Type Data	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
On Data Augmentation for Models Involving Reciprocal Gamma Functions	10
Bayesian Nowcasting with Laplacian-P-Splines	9
Convergence of Position-Dependent MALA with Application to Conditional Simulation in GLMMs	9
Scalable Estimation and Two-Sample Testing for Large Networks via Subsampling	9
Multi-label Random Subspace Ensemble Classification	9
On Inference for Modularity Statistics in Structured Networks	8
A Generalized Mean Approach for Distributed-PCA	8
Search Algorithms and Loss Functions for Bayesian Clustering	8
Scalable Feature Matching Across Large Data Collections	8
On the Use of Minimum Penalties in Statistical Learning	8
Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	8
Fast Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models	8
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	8
Enforcing Stationarity through the Prior in Vector Autoregressions	8
Massive Parallelization of Massive Sample-Size Survival Analysis	8
Competing Risk Modeling with Bivariate Varying Coefficients to Understand the Dynamic Impact of COVID-19	7
Multivariate Moment Least-Squares Variance Estimators for Reversible Markov Chains	7
Bootstrap Inference for Linear Time-Varying Coefficient Models in Locally Stationary Time Series	7
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	7
Wavelet Feature Screening	7
A Projection Approach to Local Regression with Variable-Dimension Covariates	7
A Flexible Framework for Synthesizing Categorical Sequences with Application to Human Activity Patterns	7
Correction	7
Variational Bayes in State Space Models: Inferential and Predictive Accuracy	7
Can You See The Change? Change Point Detection Using Visual Inference	7
Measure of Strength of Evidence for Visually Observed Differences between Subpopulations	7
Learning Subspaces of Different Dimensions	7
Meta Clustering for Collaborative Learning	7
Approximations in the homogeneous Ising model with application to scene analysis	6
Vecchia Likelihood Approximation for Accurate and Fast Inference with Intractable Spatial Max-Stable Models	6
More Powerful Selective Inference for the Graph Fused Lasso	6
Bayesian Distance Weighted Discrimination	6
DeepMoM: Robust Deep Learning With Median-of-Means	6
Dependent Modeling of Temporal Sequences of Random Partitions	6

A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters	6
On Exact Computation of Tukey Depth Central Regions	6
Model Checking for Logistic Models When the Number of Parameters Tends to Infinity	6
A Generalized Quantile Tree Method for Subgroup Identification	6
Accelerated Structured Matrix Factorization	6
The Mean Shape under the Relative Curvature Condition	6
Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks	6
Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model	6
Double-Matched Matrix Decomposition for Multi-View Data	6
Spatial Heterogeneous Additive Partial Linear Model: A Joint Approach of Bivariate Spline and Forest Lasso	6
Monotone Cubic B-Splines with a Neural-Network Generator	6
Universal Inference Meets Random Projections: A Scalable Test for Log-Concavity	6
Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions	6
Supervised Manifold Learning for Functional Data	6
Adaptive Semiparametric Bayesian Differential Equations Via Sequential Monte Carlo	5
Efficient Quantization Mean Estimation for Distributed Learning*	5
Deep Neural Network for Functional Graphical Models Structure Learning	5
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates	5
On the Wasserstein Median of Probability Measures	5
Scalable Inference for Hybrid Bayesian Hidden Markov Model Using Gaussian Process Emission	5
Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models	5
Nonlinear Functional Modeling Using Neural Networks	5
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects	5
A Probit Tensor Factorization Model For Relational Learning	5
Deeply Learned Generalized Linear Models with Missing Data	5
Dependence Model Assessment and Selection with DecoupleNets	5
An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression	5
Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model	5
Fluid Correlation: A Novel Nonparametric Metric to Assess the Dynamic Association	5
Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models	5
A Fast Solution to the Lasso Problem with Equality Constraints	5
Heterogeneous Functional Regression for Subgroup Analysis	4
Distributed Learning for Principal Eigenspaces without Moment Constraints	4
Simultaneous Estimation of Multiple Treatment Effects from Observational Studies	4
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data	4
Approximate Bayesian Computation with Deep Learning and Conformal prediction	4
Supervised Principal Component Regression for Functional Responses with High Dimensional Predictors	4
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	4
On Construction and Estimation of Stationary Mixture Transition Distribution Models	4
A Cepstral Model for Efficient Spectral Analysis of Covariate-Dependent Time Series	4
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	4
Co-Factor Analysis of Citation Networks	4
Nonstationary Spatial Modeling of Massive Global Satellite Data	4
Group-Orthogonal Subsampling for Hierarchical Data Based on Linear Mixed Models	4
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	4
Principal Variables Analysis for Non-Gaussian Data	4
Semiparametric Weighted Spline Regression (SWSR) in Confirmatory Clinical Trials with Time-Varying Placebo Effects	4
Big Data Model Building Using Dimension Reduction and Sample Selection	4
FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions	4
Structured Variational Approximations with Skew Normal Decomposable Graphical Models and Implicit Copulas	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
Approximating Partial Likelihood Estimators via Optimal Subsampling	4
Efficient Modeling of Spatial Extremes over Large Geographical Domains	4
Communication-Efficient Nonparametric Quantile Regression via Random Features	4
Community Detection with Heterogeneous Block Covariance Model	4
Asynchronous and Distributed Data Augmentation for Massive Data Settings	4
A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices	4
AutoGFI: Streamlined Generalized Fiducial Inference for Modern Inference Problems in Models with Additive Errors	4
Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction	4
AddiVortes: (Bayesian) Additive Voronoi Tessellations	4
A Multi-Attribute Evaluation of Genotype-Environment Experiments Using Biplots and Joint Plots Graphics	4
Hybrid Kronecker Product Decomposition and Approximation	4
Generative Quantile Regression with Variability Penalty	4
Triangular Concordance Learning of Networks	4
Correction	4
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	4
Boosting Prediction with Data Missing Not at Random	3
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	3
On Seeded Subgraph-to-Subgraph Matching: The ssSGM Algorithm and Matchability Information Theory	3
A Stability Framework for Parameter Selection in the Minimum Covariance Determinant Problem	3
Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency	3
Penguins Go Parallel: A Grammar of Graphics Framework for Generalized Parallel Coordinate Plots	3
Variational Inference Aided Variable Selection For Spatially Structured High Dimensional Covariates	3
Multiple Domain and Multiple Kernel Outcome-Weighted Learning for Estimating Individualized Treatment Regimes	3
Predictive Subdata Selection for Computer Models	3
Improved Estimation of High-dimensional Additive Models Using Subspace Learning	3
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	3
Mixtures of Matrix-Variate Contaminated Normal Distributions	3

Fast Computer Model Calibration using Annealed and Transformed Variational Inference	3
Loss-Based Variational Bayes Prediction	3
Eigen-Adjusted Functional Principal Component Analysis	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
Influential Observations Detection by Random Projection in High-Dimensional Multivariate Response Linear Model	3
Bayesian Kernel Two-Sample Testing	3
Choice of Trimming Proportion and Number of Clusters in Robust Clustering based on Trimming	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition	3
Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models	3
Ultra-Fast Approximate Inference Using Variational Functional Mixed Models	3
Statistical Inference in Circular Structural Model and Fitting Circles to Noisy Data	3
The Journal of Computational and Graphical Statistics 2023 Associate Editors	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
Variable Selection and Basis Learning for Ordinal Classification	3
Varying Coefficient Model via Adaptive Spline Fitting	3
A Simple Algorithm for Exact Multinomial Tests	3
Fast Bayesian Record Linkage for Streaming Data Contexts	3
Online Kernel-Based Mode Learning	3
Copulas and Histogram-Valued Data	3
Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm	3
Efficient Approximation of Leverage Scores in Two-Dimensional Autoregressive Models with Application to Image Anomaly Detection	3
K-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function	3
Graded Matching for Large Observational Studies	3
Features of the Polynomial Biplot for Ordered Contingency Tables	3
Generative Filtering for Recursive Bayesian Inference with Streaming Data	3
Bayesian Multilevel Network Recovery Selection	3
A Bayesian Nonparametric Stochastic Block Model for Directed Acyclic Graphs	3
Metaheuristic Solutions to Order-of-Addition Design Problems	2
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	2
Adaptive Shrinkage with a Nonparametric Bayesian Lasso	2
Supervised Stratified Subsampling for Predictive Analytics	2
Sampling Random Graphs with Specified Degree Sequences	2
Perception and Cognitive Implications of Logarithmic Scales for Exponentially Increasing Data: Perceptual Sensitivity Tested with Statistical Lineups	2
Versatile Descent Algorithms for Group Regularization and Variable Selection in Generalized Linear Models	2
Bayesian L 1/2 Regression	2
Joint Clustering With Alignment for Temporal Data in a One-Point-per-Experiment Setting	2
Smoothing Splines Approximation Using Hilbert Curve Basis Selection	2
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	2
Maximum Likelihood Estimation of Hierarchical Linear Models from Incomplete Data: Random Coefficients, Statistical Interactions, and Measurement Error	2
Simultaneous Coefficient Clustering and Sparsity for Multivariate Mixed Models	2
Efficient Sampling From the Watson Distribution in Arbitrary Dimensions	2
Optimization-based Sensitivity Analysis for Unmeasured Confounding using Partial Correlations	2
Rapid Bayesian Inference for Expensive Stochastic Models	2
Log-Rank-Type Tests for Equality of Distributions in High-Dimensional Spaces	2
Bayesian Estimation of Clustered Dependence Structures in Functional Neuroconnectivity	2
Persistence Flamelets: Topological Invariants for Scale Spaces	2
Generative Neural Networks for Characteristic Functions	2
Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models	2
Fast and Robust Low-Rank Learning over Networks: A Decentralized Matrix Quantile Regression Approach	2
Exactly Uncorrelated Sparse Principal Component Analysis	2
Nonparametric Assessment of Variable Selection and Ranking Algorithms	2
Random Forest Adjustment for Approximate Bayesian Computation	2
Adaptive Wavelet Domain Principal Component Analysis for Nonstationary Time Series	2
Functional Time Series Analysis and Visualization Based on Records	2
Copula Graphical Models for Heterogeneous Mixed Data	2
Powerful Significance Testing for Unbalanced Clusters	2
A User-Friendly Computational Framework for Robust Structured Regression with the L2 Criterion	2
Parameter Estimation of Binned Hawkes Processes	2
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods	2
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	2
An Interpretable Neural Network-based Nonproportional Odds Model for Ordinal Regression	2
Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks	2
Estimation and Model Selection for Nonparametric Function-on-Function Regression	2
A Distribution-Free Method for Change Point Detection in Non-Sparse High Dimensional Data	2
Efficient Large-Scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks	2
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives	2
smashGP: Large-Scale Spatial Modeling via Matrix-Free Gaussian Processes	2
Correction	2
A Simple Divide-and-Conquer-based Distributed Method for the Accelerated Failure Time Model	2
Doubly Adaptive Importance Sampling	2
Optimization for Calibration of Survey Weights under a Large Number of Conflicting Constraints	2
Heckman selection-contaminated normal model	2
Augmentation Samplers for Multinomial Probit Bayesian Additive Regression Trees	2
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	2
Multi-Task Learning for Gaussian Graphical Regressions with High Dimensional Covariates	2
Differentially Private Methods for Compositional Data	2
Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-Like Penalty	2
A Scalable Method to Exploit Screening in Gaussian Process Models with Noise	2
Bayesian Heterogeneous Hidden Markov Models with an Unknown Number of States	2
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning	2
When Tukey Meets Chauvenet: A New Boxplot Criterion for Outlier Detection	2
A Bootstrap-based Method for Testing Similarity of Matched Networks	2
Modeling Longitudinal Data Using Matrix Completion	2
Correspondence Analysis on Sparse Bipartite Graphs with Hyperspecialization	2
Finite Mixtures of Multivariate Contaminated Normal Censored Regression Models	2
Gibbs Priors for Bayesian Nonparametric Variable Selection with Weak Learners	2
Scalable Estimation for Structured Additive Distributional Regression	1
Generative Multi-Purpose Sampler for Weighted M-estimation	1
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	1
Network Embedding-based Directed Community Detection with Unknown Community Number	1
Stochastic Block Smooth Graphon Model	1
Interpretable Architecture Neural Networks for Function Visualization	1
Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data	1