yusuke1997/dblp-id-title huggingface dataset:
Generating random numbers from a distribution specified by its Laplace transform
A probabilistic model for the numerical solution of initial value problems
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems
Bootstrap-based statistical inference on the eigenvalues of weighted networks
Generalized spherical principal component analysis
Discriminative clustering with representation learning with any ratio of labeled to unlabeled data
Parallelizing MCMC for Bayesian spatiotemporal geostatistical models
Stochastic variational inference for GARCH models
Bayesian neural networks for nonlinear time series forecasting
Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection
Simplifying the calculation of the P-value for Barnard's test and its derivatives
Characterization of topic-based online communities by combining network data and user generated content
A search of maximum generalized resolution quaternary-code designs via integer linear programming
Computation of Gaussian orthant probabilities in high dimension
Bootstrap techniques for proportional hazards models with censored observations
Robust online-surveillance of trend-coherence in multivariate data streams: the similar trend monitoring (STM) procedure
Fast approximate Bayesian computation for estimating parameters in differential equations
Beta kernel quantile estimators of heavy-tailed loss distributions
Generating generalized inverse Gaussian random variates
A Spectral Estimator of Arma Parameters from Thresholded Data
Optimal confidence interval for the difference between proportions
Sampling from multimodal distributions using tempered transitions
Multi-step variance minimization in sequential tests
Partial cell suppression: A new methodology for statistical disclosure control
Finite mixtures of canonical fundamental skew t-distributions - The unification of the restricted and unrestricted skew t-mixture models
Nonnegative Bayesian nonparametric factor models with completely random measures
Estimation and variable selection in nonparametric heteroscedastic regression
Nonparametric self-exciting models for computer network traffic
Detecting Structural Shifts and Estimating Single Change-Points in Interval-Based Time Series
Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components
A dynamic EM algorithm for estimating mixture proportions
Bayesian parameter estimation via variational methods
Multiple-output quantile regression neural network
Optimal orthogonal designs for experiments with four-level and two-level factors
Clustering for contingency tables: boxes and partitions
Regularizing axis-aligned ensembles via data rotations that favor simpler learners
Nonlinear principal component analysis for two-dimensional functional data using neural networks
Rule generation for categorical time series with Markov assumptions
An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models
Weight-preserving simulated tempering
Antithetic and Monte Carlo kernel estimators for partial rankings
Efficient Monte Carlo simulation via the generalized splitting method
Analysis of the Gibbs sampler for a model related to James-Stein estimators
A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data
Bias-reduced and variance-corrected asymptotic Gaussian inference about extreme expectiles
A review on the Adaptive-Ridge Algorithm with several extensions
A constrained regression model for an ordinal response with ordinal predictors
Improving the prediction accuracy of statistical models: A new hierarchical clustering approach
Metrics and barycenters for point pattern data
Shrinkage estimation of varying covariate effects based on quantile regression
Bayesian additive regression trees with model trees
A novel and fast methodology for simultaneous multiple structural break estimation and variable selection for nonstationary time series models
An adaptive truncation method for inference in Bayesian nonparametric models
Model averaging for support vector classifier by cross-validation
On the Deng-Lin random number generators and related methods
Conditional vs marginal estimation of the predictive loss of hierarchical models using WAIC and cross-validation
Editor's note: special section on Bayesian Nonparametrics
Estimation of extreme quantiles from heavy-tailed distributions with neural networks
Modified explicit inversive congruential pseudorandom numbers with power of 2 modulus
Learning from data's evolution in normal equations: the DECK-principle and equations' adjustment
Efficient estimation for varying coefficient modal regression
Estimation of parameters for trend-renewal processes
Likelihood-free inference via classification
Automatic search intervals for the smoothing parameter in penalized splines
Time-course window estimator for ordinary differential equations linear in the parameters
A semi-parametric additive model for variance heterogeneity
Procrustes shape analysis of triangulations of a two coloured point pattern
Sparse Bayesian learning for label efficiency in cardiac real-time MRI
Two-tailed approximate confidence intervals for the ratio of proportions
Bayesian variable selection for matrix autoregressive models
Double-Parallel Monte Carlo for Bayesian analysis of big data
RSFclust: Robust sparse clustering of functional data using quantile curves
Correction to: analysis of stochastic gradient descent in continuous time
Global sensitivity analysis using complex linear models
Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms
Statistical analysis of differential equations: introducing probability measures on numerical solutions
One-step closed-form estimator for generalized linear model with categorical explanatory variables
Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm
Directional data analysis: spherical Cauchy or Poisson kernel-based distribution?
Scalable computations for nonstationary Gaussian processes
An improved Hara-Takamura procedure by sharing computations on junction tree in Gaussian graphical models
Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image time-series
Massively parallel computing: a statistical application
Mixture structure analysis using the Akaike Information Criterion and the bootstrap
Clustering time series by linear dependency
A multiscale method for data collected from network edges via the line graph
ROC curve and covariates: extending induced methodology to the non-parametric framework
Empirical investigations of boosting with pseudo-outcome imputation for missing responses
Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural networks
Robust multipe imputation with GAM
Simulation-based inference for simultaneous processes on regular lattices
Variance reduction for Markov chains with application to MCMC
A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions
On the application of Gaussian graphical models to paired data problems
Removal of redundant candidate points for the exact D-optimal design problem
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization
Generalised joint regression for count data: a penalty extension for competitive settings
Finite mixtures of multivariate Poisson-log normal factor analyzers for clustering count data
Detecting anomalies in fibre systems using 3-dimensional image data
Non-binary classification trees
Inference in finite state space non parametric Hidden Markov Models and applications
Semiparametric efficient estimation of genetic relatedness with machine learning methods
Optimal experimental design for linear time invariant state-space models
Introduction to "Efficient local updates for undirected graphical models" by F. Stingo, G. Marchetti
Segmental dynamic factor analysis for time series of curves
Distributed empirical likelihood inference with or without Byzantine failures
GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model
High-dimensional VAR with low-rank transition
Bayesian analysis of the unobserved ARCH model
Numerical approaches to finite-horizon optimal stopping problems for the Shiryaev process
Laplace-based strategies for Bayesian optimal experimental design with nuisance uncertainty
On the identifiability of Bayesian factor analytic models
From sparse to dense functional data: phase transitions from a simultaneous inference perspective
Space-time generation of high intensity patterns using growth-interaction processes
Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins
A comparison of dependence function estimators in multivariate extremes
Estimating likelihoods for spatio-temporal models using importance sampling
Spatial variability clustering for spatially dependent functional data
A flexible and tractable class of one-factor copulas
Markov chain Monte Carlo methods for family trees using a parallel processor
Fast sampling from β-ensembles
Transformation boosting machines
Probabilistic 'generalization' of functions and dimension-based uniform convergence results
Bayesian inference for Heston-STAR models
Detecting and diagnosing prior and likelihood sensitivity with power-scaling
Causal Segment Regression with Multiple Thresholds
ADE-4: a multivariate analysis and graphical display software
Detection of structurally homogeneous subsets in graphs
Semiparametric transformation models with Bayesian P-splines
Consistent online Gaussian process regression without the sample complexity bottleneck
Uncertainty Quantification for Linear Inverse Problems with Besov Prior: A Randomize-Then-Optimize Method
Bayesian kernel projections for classification of high dimensional data
A boosting framework for positive-unlabeled learning
Direct sampling with a step function
DRAM: Efficient adaptive MCMC
Estimating large-scale general linear and seemingly unrelated regressions models after deleting observations
Estimating the number of true null hypotheses based on change point of observed p values
Variational Bayes with synthetic likelihood
Introduction to "On the use of Markov chain Monte Carlo methods for the sampling of mixture models" by R. Douc, F. Maire, J. Olsson
Nudging state-space models for Bayesian filtering under misspecified dynamics
MAD-STEC: a method for multiple automatic detection of space-time emerging clusters
Matrix completion with nonconvex regularization: spectral operators and scalable algorithms
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models
Approximating cross-validatory predictive evaluation in Bayesian latent variable models with integrated IS and WAIC
Discretisation for inference on normal mixture models
Pivotal variable detection of the covariance matrix and its application to high-dimensional factor models
Pairwise likelihood estimation for multivariate mixed Poisson models generated by Gamma intensities
A fast unified algorithm for solving group-lasso penalize learning problems
Bounded-memory adjusted scores estimation in generalized linear models with large data sets
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration
On parallelizable Markov chain Monte Carlo algorithms with waste-recycling
Two-level D- and A-optimal main-effects designs with run sizes one and two more than a multiple of four
Sequential change detection in the presence of unknown parameters
Bayesian spatiotemporal modeling for inverse problems
A rare event approach to high-dimensional approximate Bayesian computation
Heterogeneous analysis for clustered data using grouped finite mixture models
On parallel implementation of sequential Monte Carlo methods: the island particle model
Bayesian marginal inference via candidate's formula
The use of a single pseudo-sample in approximate Bayesian computation
A Bayesian model for local smoothing in kernel density estimation
Spike and slab Bayesian sparse principal component analysis
Estimating the causal treatment effect in multi-site current status data with the additive hazards model and neural networks
A multivariate uniformity test for the case of unknown support
Latent uniform samplers on multivariate binary spaces
COPICA - independent component analysis via copula techniques
Sparse estimation via nonconcave penalized likelihood in factor analysis model
Latent structure blockmodels for Bayesian spectral graph clustering
Individualized treatment rules based on adaptive transfer-dragonnet
Secure Bayesian model averaging for horizontally partitioned data
Classification of cyclical time series using complex demodulation
Random coefficient models for binary longitudinal responses with attrition
General Jackknife empirical likelihood and its applications
Variational Tobit Gaussian Process Regression
The node-wise Pseudo-marginal method: model selection with spatial dependence on latent graphs
A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs
Estimation and regularization techniques for regression models with multidimensional prediction functions
Flexible Bayesian modeling for longitudinal binary and ordinal responses
Bayesian analysis of mixture modelling using the multivariate t distribution
Nonlinear Functional Sufficient Dimension Reduction via Principal Fitted Components
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming
Inferring large graphs using ℓ 1 -penalized likelihood
A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference
Robust nonlinear principal components
Uniform calibration tests for forecasting systems with small lead time
Review of the Stata statistical package
Prediction-based regularization using data augmented regression
Simulation of right and left truncated gamma distributions by mixtures
A network epidemic model for online community commissioning data
Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks
Saturated main-effect designs for factorial experiments
Calculating the density and distribution function for the singly and doubly noncentral F
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion
Stochastic three-term conjugate gradient method with variance technique for non-convex learning
Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method
A comparison of estimators for regression models with change points
A model identification and selection method for varying coefficient EV models with missing responses
The stochastic proximal distance algorithm
DGP-LVM: Derivative Gaussian process latent variable models
Suppressing marginal totals from a two-dimensional table to protect sensitive information
Robust estimation of the correlation matrix of longitudinal data
Stochastic proximal-gradient algorithms for penalized mixed models
Penalized estimation of directed acyclic graphs from discrete data
Density regression via Dirichlet process mixtures of normal structured additive regression models
Bivariate conditioning approximations for multivariate normal probabilities
On simulation of continuous determinantal point processes
Location adjustment for the minimum volume ellipsoid estimator
Discussion on the paper by Friedman and Fisher
The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere
Quasi-random numbers for copula models
Copula regression spline models for binary outcomes
Symmetry exploits for Bayesian cubature methods
Generalized EM estimation for semi-parametric mixture distributions with discretized non-parametric component
Sequential parameter learning and filtering in structured autoregressive state-space models
Confidence graphs for graphical model selection
Robust feature screening via Grothendieck's correlation with FDR control
Maximin design on non hypercube domains and kernel interpolation
Neighborhood graphs, stripes and shadow plots for cluster visualization
Bayesian longitudinal item response modeling with restricted covariance pattern structures
High-dimensional regression with potential prior information on variable importance
Estimation and selection for the latent block model on categorical data
Control variates for stochastic gradient MCMC
Quantile-based fitting for graph signals
Accelerating the estimation of renewal Hawkes self-exciting point processes
Functional sufficient dimension reduction with multivariate responses: a projection averaging method and beyond
Network-assisted Semi-supervised Logistic Regression
Enhancing cure rate analysis through integration of machine learning models: a comparative study
Improved bridge constructs for stochastic differential equations
Multiscale interpretation of taut string estimation and its connection to Unbalanced Haar wavelets
Particle gradient descent model for point process generation
Semi-automated simultaneous predictor selection for regression-SARIMA models
Detecting renewal states in chains of variable length via intrinsic Bayes factors
Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models
On the discretization of nonparametric isotropic covariogram estimators
Significativity Indices for Agreement Values
Efficient probabilistic reconciliation of forecasts for real-valued and count time series
Reparameterization strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation
Projection techniques for nonlinear principal component analysis
Group sparse structural smoothing recovery: model, statistical properties and algorithm
Introduction to "On a class of σ-stable Poisson-Kingman models and an effective marginalized sampler" by S. Favaro, M. Lomeli, Y. W. Teh
The EM algorithm with gradient function update for discrete mixtures with known (fixed) number of components
Slice sampling mixture models
Central quantile subspace
A case study of the widely applicable Bayesian information criterion and its optimality
A new functional statistic for multivariate normality
Hybrid methods for calculating optimal few-stage sequential strategies: Data monitoring for a clinical trial
Extreme value modeling with errors-in-variables in detection and attribution of changes in climate extremes
Flexible Bayesian quantile regression based on the generalized asymmetric Huberised-type distribution
T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method
A robust and efficient algorithm to find profile likelihood confidence intervals
Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation
Matrix regression heterogeneity analysis
Robust and Efficient Estimation for the Block-Basu Bivariate Exponential Distribution
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors
Multiscale local polynomial decompositions using bandwidths as scales
Selection of sparse vine copulas in high dimensions with the Lasso
Robust and missing-data-aware time-varying graphical lasso(RM-TVGL) for high-dimensional dynamic network estimation
Certified coordinate selection for high-dimensional Bayesian inversion with Laplace prior
Robust variable selection for partially linear additive models
Prior specification for binary Markov mesh models
A guided walk Metropolis algorithm
Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors
Generalised likelihood profiles for models with intractable likelihoods
Hypothesis testing for Markov chain Monte Carlo
SiZer Map for inference with additive models
On the f-divergences between densities of a multivariate location or scale family
Do applied statisticians prefer more randomness or less? Bootstrap or Jackknife?
Generalized parallel tempering on Bayesian inverse problems
Mixture models for ordinal data: a pairwise likelihood approach
Editor's note: 25th Anniversary Special Issue
A tutorial on adaptive MCMC
Efficient local updates for undirected graphical models
Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models
Coverage plots for assessing the variability of estimated contours of a density
Maximum likelihood estimation of log-concave densities on tree space
A point mass proposal method for Bayesian state-space model fitting
Deterministic versus stochastic seasonal fractional integration and structural breaks
Applying classification algorithms in practice
Generalized linear mixed models for correlated binary data with t-link
Discussion of papers by Dempster and Aitkin
A numerically stable algorithm for integrating Bayesian models using Markov melding
Coupling random inputs for parameter estimation in complex models
Adaptive importance sampling in general mixture classes
A framework for mediation analysis with massive data
On a convergent stochastic estimation algorithm for frailty models
Online structural break detection in financial durations
Editorial: Statistics and computing: Having an impact
Birnbaum-Saunders frailty regression models for clustered survival data
Guest Editorial: Computational Issues in Experimental Design
Gaussian process learning via Fisher scoring of Vecchia's approximation
Wiener-type integral approximation for sampling distributions of irregularly spaced spatial data
Coordinate descent algorithm for covariance graphical lasso
Correction to: A two-stage Bayesian semiparametricmodel for novelty detection with robust prior information
Use generalized linear models or generalized partially linear models?
Empirical geodesic graphs and CAT(k) metrics for data analysis
Vine copula approximation: a generic method for coping with conditional dependence
On approximations of subordinators in L p and the simulation of tempered stable distributions
A Joint estimation approach to sparse additive ordinary differential equations
Finding overlapping components with MML
funBIalign: a hierachical algorithm for functional motif discovery based on mean squared residue scores
Guest editorial: Image analysis
Parametric and permutation testing for multivariate monotonic alternatives
A new variable importance measure for random forests with missing data
Gradient boosting for generalised additive mixed models
Variable selection and regularization via arbitrary rectangle-range generalized elastic net
Sequential Monte Carlo on large binary sampling spaces
Outlier detection in non-elliptical data by kernel MRCD
Bayesian MARS
Non-linear regression models for Approximate Bayesian Computation
Sequential importance sampling of binary sequences
Robustness of automated data choices of smoothing parameter in image regularization
The ensemble Kalman filter is an ABC algorithm
Asymptotic normality of extensible grid sampling
Some computational aspects of Gaussian CARMA modelling
Large-scale constrained Gaussian processes for shape-restricted function estimation
An efficient implementation of the ensemble Kalman filter based on an iterative Sherman-Morrison formula
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance
Uniform random generation of large acyclic digraphs
Fitting Kent models to compositional data with small concentration
Screen then select: a strategy for correlated predictors in high-dimensional quantile regression
An adaptive approach to Langevin MCMC
New recursive estimators of the time-average variance constant
Fast Bayesian inversion for high dimensional inverse problems
Statistical Analysis of Dissimilarity Matrices
The predictive Lasso
Bootstrap estimation of actual significance levels for tests based on estimated nuisance parameters
Random effects selection in generalized linear mixed models via shrinkage penalty function