yusuke1997/dblp-id-title huggingface dataset:
Tuning diagonal scale matrices for HMC
Monte Carlo methods for approximating a posterior hazard rate process
Systemic infinitesimal over-dispersion on graphical dynamic models
Estimation of long-range dependence in gappy Gaussian time series
Implicitly adaptive importance sampling
Gauss-Christoffel quadrature for inverse regression: applications to computer experiments
On the computation of the noncentral F and noncentral beta distribution
Identification of partly destroyed objects using deformable templates
Two-armed Bandit Bootstrap for Model-free Equivalent Rank Test
Spatial J-test: some Monte Carlo evidence
Parallelizing MCMC sampling via space partitioning
Robust singular value decomposition with application to video surveillance background modelling
Mixture separation for mixed-mode data
A semi-infinite programming based algorithm for finding minimax optimal designs for nonlinear models
Variational Bayes on manifolds
Weighted composite likelihood-based tests for space-time separability of covariance functions
Lévy Langevin Monte Carlo
Fast covariance estimation for high-dimensional functional data
Bayesian contiguity constrained clustering
Factored principal components analysis, with applications to face recognition
Deep Gaussian mixture models
Structured regularization for conditional Gaussian graphical models
The recursive variational Gaussian approximation (R-VGA)
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport
Maximum entropy simulation for microdata protection
Multiple-index approach to multiple autoregressive time series model
Does data splitting improve prediction?
A comparison of methods for the fitting of generalized additive models
Uncertainty modelling and computational aspects of data association
Semi-parametric extended Poisson process models for count data
A non-iterative optimization method for smoothness in penalized spline regression
Individualized causal mediation analysis with continuous treatment using conditional generative adversarial networks
Parsimonious mixtures for the analysis of tensor-variate data
Modeling continuous shape change for facial animation
The Gaussian rank correlation estimator: robustness properties
Penalized regression with correlation-based penalty
Model-based clustering with missing not at random data
Partitioning predictors in multivariate regression models
Restricted likelihood ratio tests for linearity in scalar-on-function regression
Fast adaptive Fourier integration for spectral densities of Gaussian processes
A Laplace-based algorithm for Bayesian adaptive design
Modifications of REML algorithm for HGLMs
Multi-scale process modelling and distributed computation for spatial data
Exploratory factor and principal component analyses: some new aspects
Goodness of fit in relational event models
Modified repeated median filters
The sparse dynamic factor model: a regularised quasi-maximum likelihood approach
A comparison study of nonparametric imputation methods
Particle methods for maximum likelihood estimation in latent variable models
Testing for additivity and joint effects in multivariate nonparametric regression using Fourier and wavelet methods
Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation
Flexible parametric bootstrap for testing homogeneity against clustering and assessing the number of clusters
Global-local shrinkage multivariate logit-beta priors for multiple response-type data
Learning a multivariate Gaussian mixture model with the reversible jump MCMC algorithm
An efficient method to simulate diffusion bridges
An introduction to the special issue "Joint IMS-ISBA meeting - MCMSki 4"
Constructing optimal designs for fitting pharmacokinetic models
Model-free feature screening for ultrahigh dimensional censored regression
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models
Multivariate sufficient statistics using Kronecker products
A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions
Bayesian model selection for analyzing predictor-dependent directional data
A multifacet hierarchical sentiment-topic model with application to multi-brand online review analysis
Editorial: Special issue on adaptive Monte Carlo methods
Consistency factor for the MCD estimator at the Student-t distribution
Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic student-t model
Combinatorial analysis of the adaptive last particle method
Variable selection using conditional AIC for linear mixed models with data-driven transformations
Series evaluation of Tweedie exponential dispersion model densities
Identifying Collapsible Sets in Directed Graphical Models via Inducing Paths
A review and some new results on permutation testing for multivariate problems
Finite mixtures of matrix normal distributions for classifying three-way data
Biclustering via structured regularized matrix decomposition
Boosted coefficient models
A comparison of six methods of analysing row-column designs with inter-block information
Hidden Markov models with state-dependent mixtures: minimal representation, model testing and applications to clustering
A joint latent factor analyzer and functional subspace model for clustering multivariate functional data
Multivariate and regression models for directional data based on projected Pólya trees
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions
A blocked Gibbs sampler for NGG-mixture models via a priori truncation
Rejection sampling for tempered Lévy processes
Analysis of adaptive directional stratification for the controlled estimation of rare event probabilities
On population-based simulation for static inference
Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy
A consistent and numerically efficient variable selection method for sparse Poisson regression with applications to learning and signal recovery
Model-based clustering with sparse covariance matrices
A general maximum likelihood analysis of measurement error in generalized linear models
Relative error model average for multiplicative models
Clustering via nonparametric density estimation
Improved nearest neighbor classifiers by weighting and selection of predictors
A piecewise deterministic Monte Carlo method for diffusion bridges
Principal components analysis of nonstationary time series data
Fast bayesian variable screening using correlation thresholds
Information preservation with wasserstein autoencoders: generation consistency and adversarial robustness
Data-driven Kriging models based on FANOVA-decomposition
Deep neural networks for variable selection of higher-order nonparametric spatial autoregressive model
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Approximation and sampling of multivariate probability distributions in the tensor train decomposition
Stochastic variational inference for scalable non-stationary Gaussian process regression
Bayesian additive tree ensembles for composite quantile regressions
Nonlinear kernel density principal component analysis with application to climate data
A 'nondecimated' lifting transform
Type I Tobit Bayesian Additive Regression Trees for censored outcome regression
Hausdorff correlation for interval-valued random objects
Sparse functional partial least squares regression with a locally sparse slope function
Modified Hamiltonian Monte Carlo for Bayesian inference
Gaussian measures conditioned on nonlinear observations: consistency, MAP estimators, and simulation
Estimating means when sampling gives probabilities as well as values or "Looking a gift horse in the mouth"
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering
Local linear regression with adaptive orthogonal fitting for the wind power application
Estimating curves and derivatives with parametric penalized spline smoothing
The Statistics of Simulating Chaos
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes
S-SIRUS: an explainability algorithm for spatial regression Random Forest
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers
Perfect simulation of positive Gaussian distributions
Univariate Bayesian nonparametric mixture modeling with unimodal kernels
A two-sample empirical likelihood ratio test based on samples entropy
Smoothing combined estimating equations in quantile regression for longitudinal data
Conditional simulation for moving average processes with discrete or continuous values
Editorial: special edition on probabilistic numerics
An approach to non-linear principal components analysis using radially symmetric kernel functions
Fast parallel α-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs
Hidden Markov models for multivariate panel data
Thermodynamic Bayesian model comparison
Perfect sampling algorithm for small m × n contingency tables
Exploiting low-rank covariance structures for computing high-dimensional normal and Student-t probabilities
Robust adaptive Metropolis algorithm with coerced acceptance rate
Tree based credible set estimation
Over-relaxation methods and coupled Markov chains for Monte Carlo simulation
The limited-memory recursive variational Gaussian approximation (L-RVGA)
Variational inference for Bayesian bridge regression
Conditional Graphical Models With A Hierarchical Sparse Estimation
On the exact maximum likelihood inference of Fisher-Bingham distributions using an adjusted holonomic gradient method
Composable models for online Bayesian analysis of streaming data
Online signal extraction by robust regression in moving windows with data-adaptive width selection - SCARM - Slope Comparing Adaptive Repeated Median
Partitioned algorithms for maximum likelihood and other non-linear estimation
Matching estimators and optimal bandwidth choice
Option pricing under model and parameter uncertainty using predictive densities
False discovery rate envelopes
Forecasting with non-homogeneous hidden Markov models
A Bayesian method for identifying independent sources of non-random spatial patterns
Automated selection of r for the r largest order statistics approach with adjustment for sequential testing
It's been great - and the future looks even better
ECOPICA: empirical copula-based independent component analysis
Exact average coverage probabilities and confidence coefficients of confidence intervals for discrete distributions
Multilevel importance sampling for rare events associated with the McKean-Vlasov equation
A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: application to robust clustering
The computational asymptotics of Gaussian variational inference and the Laplace approximation
Remote access systems for statistical analysis of microdata
Recent trends and developments in computational multivariate analysis
A structured Dirichlet mixture model for compositional data: inferential and applicative issues
A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models
Bayesian estimation of quantile distributions
A note on the non-negativity of continuous-time ARMA and GARCH processes
A Bayesian Model for Co-clustering Ordinal Data with Informative Missing Entries
Adaptive grid semidefinite programming for finding optimal designs
LASSO-type estimators for semiparametric nonlinear mixed-effects models estimation
Density-based Silhouette diagnostics for clustering methods
Partial replacement imputation estimation for partially linear models with complex missing pattern covariates
Adaptive step size rules for stochastic optimization in large-scale learning
A new algorithm to estimate monotone nonparametric link functions and a comparison with parametric approach
Optimal distributed subsampling under heterogeneity
Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter
A general model-checking procedure for semiparametric accelerated failure time models
Proximal nested sampling for high-dimensional Bayesian model selection
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization
Penalized principal component analysis using smoothing
A permutation approach for testing heterogeneity in two-sample categorical variables
A novel method for constructing ensemble classifiers
An advancement in clustering via nonparametric density estimation
Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models
The minimum covariance determinant estimator for interval-valued data
Information-Theoretic Criteria for Optimizing Designs of Individually Randomized Stepped-Wedge Clinical Trials
Quantile hidden semi-Markov models for multivariate time series
Probabilistic relabelling strategies for the label switching problem in Bayesian mixture models
Optimal exact designs of experiments via Mixed Integer Nonlinear Programming
Numerical computation of rectangular bivariate and trivariate normal and t probabilities
An algorithm aiming at unimodal density-based clustering using Gaussian mixture models
Restricted Indian buffet processes
Cluster analysis of massive datasets in astronomy
A computational procedure for estimation of the mixing time of the random-scan Metropolis algorithm
Variational approximation for heteroscedastic linear models and matching pursuit algorithms
Sklar's Omega: A Gaussian copula-based framework for assessing agreement
Estimating second order characteristics of point processes with known independent noise
Local principal curves
GIPSCAL revisited. A projected gradient approach
Efficient MCMC sampling in dynamic mixture models
Transfer learning for high-dimensional data with heavy-tailed noise: A sparse convoluted rank regression method
A second-order iterated smoothing algorithm
Nonlinear sufficient dimension reduction for Conditional quantiles in scalar-on-function single-index models
Improved auxiliary mixture sampling for hierarchical models of non-Gaussian data
Erratum to: Two-tailed approximate confidence intervals for the ratio of proportions
Wavelet shrinkage for unequally spaced data
Straightforward intermediate rank tensor product smoothing in mixed models
Estimation of time-varying autoregressive stochastic volatility models with stable innovations
Multivariate zero-inflated INGARCH models: Bayesian inference and composite likelihood approach
High-dimensional missing data imputation via undirected graphical model
Model-based adaptive spatial sampling for occurrence map construction
On weak convergence of quantile-based empirical likelihood process for ROC curves
Evaluation of combinatorial optimisation algorithms for c-optimal experimental designs with correlated observations
Analysis of stochastic gradient descent in continuous time
Computing projection depth and its associated estimators
Adaptive particle allocation in iterated sequential Monte Carlo via approximating meta-models
Using a correlated probit model approximation to estimate the variance for binary matched pairs
Adaptive sequential Monte Carlo by means of mixture of experts
QuickMMCTest: quick multiple Monte Carlo testing
Exploring the number of groups in robust model-based clustering
Efficient use of exact samples
Bayesian semiparametric modeling and inference with mixtures of symmetric distributions
Nested Kriging predictions for datasets with a large number of observations
Guest editorial: Semiparametric function estimation and testing
Regression analysis with partially labelled regressors: carbon dating of the Shroud of Turin
Diffusive nested sampling
New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes
Initializing EM using the properties of its trajectories in Gaussian mixtures
A moment-matching Ferguson & Klass algorithm
Imputation and low-rank estimation with Missing Not At Random data
Topology-driven goodness-of-fit tests in arbitrary dimensions
A fast and accurate numerical method for the left tail of sums of independent random variables
Double-loop importance sampling for McKean-Vlasov stochastic differential equation
Model based labeling for mixture models
Wasserstein k-Centers Clustering for Distributional Data
A standardized distance-based index to assess the quality of space-filling designs
Parsimonious consensus hierarchies, partitions and fuzzy partitioning of a set of hierarchies
Computer experiments with functional inputs and scalar outputs by a norm-based approach
Isometric sliced inverse regression for nonlinear manifold learning
Sequential Monte Carlo for counting vertex covers in general graphs
Evaluation of the run-length distribution for a combined Shewhart-EWMA control chart
Estimation of ratios of normalizing constants using stochastic approximation: the SARIS algorithm
A note on auxiliary mixture sampling for Bayesian Poisson models
Flexible mixture modelling using the multivariate skew-t-normal distribution
Introduction to "Cuts in Bayesian graphical models" by M. Plummer
Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data
Two-Metric Variable Scaled Splitting Algorithm for Nonsmooth Nonconvex Sparsity-penalized Quantile Regression
Tree-structured modelling of varying coefficients
Sparse outlier-robust PCA for multi-source data
Maximal autocorrelation functions in functional data analysis
Sequential Bayesian optimal experimental design for structural reliability analysis
Evaluation of Gaussian orthant probabilities based on orthogonal projections to subspaces
Split Hamiltonian Monte Carlo
Estimating a sparse reduction for general regression in high dimensions
Data-driven uncertainty quantification for constrained stochastic differential equations and application to solar photovoltaic power forecast data
Bayesian quantile regression for single-index models
Distributed Estimation and Algorithm for Distributed Outcome Dependent Subsampling in Generalized Linear Regression with Large-scale Data
Quantile generalized measures of correlation
Objective Bayesian transformation and variable selection using default Bayes factors
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes
Testing implication of hierarchical log-linear models for probability distributions
Majorization minimization by coordinate descent for concave penalized generalized linear models
Erratum to: Localizing the latent structure canonical uncertainty: entropy profiles for hidden Markov models
Modeling volatility for high-frequency data with rounding error: a nonparametric Bayesian approach
Asymmetry models for square contingency tables: exact tests via algebraic statistics
Tree-based variational inference for Poisson log-normal models
Estimation of conditional quantiles by a new smoothing approximation of asymmetric loss functions
Nonparametric empirical bayes prediction in mixed models
Bayesian estimation and stochastic model specification search for dynamic survival models
Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics
DeepJAM: Joint alignment of multivariate quasi-periodic functional data using deep learning
Sequential Bayesian Registration for Functional Data
Segmentation uncertainty in multiple change-point models
Byzantine-robust and efficient distributed sparsity learning: a surrogate composite quantile regression approach
DINDSCAL: direct INDSCAL
Bayesian projection pursuit regression
A model of Poissonian interactions and detection of dependence
A likelihood ratio test of a homoscedastic normal mixture against a heteroscedastic normal mixture
The algebra of interpolatory cubature formulæ for generic nodes
An alternative to model selection in ordinary regression
Search for optimal designs in a three stagenested random model
Fast and universal estimation of latent variable models using extended variational approximations
Graph sub-sampling for divide-and-conquer algorithms in large networks
Comparison of Bayesian predictive methods for model selection
Latent mixture modeling for clustered data
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
Adaptive wavelet series estimation in separable nonparametric regression models
A neural network-based adaptive cut-off approach to normality testing for dependent data
Multi-dimensional functional principal component analysis
Quantile ratio regression
Improved cross-entropy method for estimation
APPLE: approximate path for penalized likelihood estimators
A Bayesian nonparametric Markovian model for non-stationary time series
Sampling from Conditional Distributions of Simplified Vines
Hierarchical Mixtures of Latent Trait Analyzers with concomitant variables for multivariate binary data
Symbolic Itô calculus in AXIOM: An ongoing story
Estimation of a likelihood ratio ordered family of distributions
A SAEM algorithm for the estimation of template and deformation parameters in medical image sequences
Simultaneous model-based clustering and visualization in the Fisher discriminative subspace
Pareto-efficient designs for multi- and mixed-level supersaturated designs
An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data
Maximum likelihood estimation of the Fisher-Bingham distribution via efficient calculation of its normalizing constant
Bayesian parameter inference for partially observed stochastic volterra equations
Langevin incremental mixture importance sampling
The one-step-late PXEM algorithm
On learning strategies for evolutionary Monte Carlo
MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression
Sparse Bayesian learning using TMB (Template Model Builder)
An interchange algorithm for four factor orthogonal main effect plans
Efficient Bayesian inference for COM-Poisson regression models
A wavelet lifting approach to long-memory estimation
An improved bisection-type algorithm for control chart calibration
Fitting Matérn smoothness parameters using automatic differentiation
Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation
Numerical optimization and surface estimation with imprecise function evaluations
Parsimonious hidden Markov models for matrix-variate longitudinal data
Sparse estimation and inference for prediction-powered semi-supervised linear regression
Fast simulation of truncated Gaussian distributions
Estimating and testing zones of abrupt change for spatial data
Measuring dependence between functional data via Projection Hilbert-Schmidt Covariance
Clustering validation by distribution hypothesis learning
Estimation and model selection for finite mixtures of Tukey's g- &-h distributions
Orthodox BLUP versus h-likelihood methods for inferences about random effects in Tweedie mixed models
Model selection for probabilistic clustering using cross-validated likelihood
Multi-task learning via robust regularized clustering with non-convex group penalties
Graph-based algorithms for phase-type distributions
Bayesian inference for multivariate gamma distributions
Delete-m Jackknife for Unequal m
Statistical mechanical analysis of the dynamics of learning in perceptrons
Sequential Monte Carlo with transformations
Dynamic stochastic block models: parameter estimation and detection of changes in community structure
3D object recognition: Representation and matching
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence
Local bandwidth selectors for deconvolution kernel density estimation
A simulated annealing approach to approximate Bayes computations
Pre-processing for approximate Bayesian computation in image analysis
Random perturbation subsampling for rank regression with massive data
The structured elastic net for quantile regression and support vector classification
Edge selection based on the geometry of dually flat spaces for Gaussian graphical models