yusuke1997/dblp-id-title huggingface dataset:
Introduction to "Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks" by A. Caimo, A. Mira
Robust Bayesian model selection for variable clustering with the Gaussian graphical model
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm
Efficient sampling schemes for Bayesian MARS models with many predictors
Efficient recursive algorithms for functionals based on higher order derivatives of the multivariate Gaussian density
Functional autoencoder for smoothing and representation learning
Gaussian processes for Bayesian inverse problems associated with linear partial differential equations
Penalized semiparametric density estimation
A first-order algorithm for the A-optimal experimental design problem: a mathematical programming approach
Parsimonious periodic autoregressive models for time series with evolving trend and seasonality
MDL convergence speed for Bernoulli sequences
Localized classification
Huber-energy measure quantization
Model-based clustering of time-dependent observations with common structural changes
Likelihood-based surrogate dimension reduction
Hybrid elicitation and quantile-parametrized likelihood
Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function
On coupling particle filter trajectories
Exact estimation of multiple directed acyclic graphs
Parameter estimation of complex mixed models based on meta-model approach
Gaussian proposal density using moment matching in SMC methods
Testing symmetry for bivariate copulas using Bernstein polynomials
Automatic specification of piecewise linear additive models: application to forecasting natural gas demand
Information preserving regression-based tools for statistical disclosure control
Cauchy robust principal component analysis with applications to high-dimensional data sets
A computationally efficient nonparametric approach for changepoint detection
Low-rank regularization of global fréchet regression models for distributional responses
Long memory and changepoint models: a spectral classification procedure
Estimation of finite mixtures with symmetric components
On Bayesian nonparametric modelling of two correlated distributions
Iterative bias reduction: a comparative study
Sequential Bayesian inference in hidden Markov stochastic kinetic models with application to detection and response to seasonal epidemics
Conditional density estimation using the local Gaussian correlation
The minimum regularized covariance determinant estimator
Slope heuristics: overview and implementation
A tutorial on spectral clustering
On the positivity and magnitudes of Bayesian quadrature weights
Mean likelihood estimators
A framework of regularized low-rank matrix models for regression and classification
A semiparametric approach to hidden Markov models under longitudinal observations
Stochastic approximation cut algorithm for inference in modularized Bayesian models
Semi-parametric forecasts of the implied volatility surface using regression trees
Exact score and information matrix for panel hidden semi-Markov models
A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments
A Laplace transform inversion method for probability distribution functions
On the distribution of linear combinations of independent Gumbel random variables
Multivariate two-sample tests via random projection
Accuracy of edge detection methods with local information in speckled imagery
High-dimensional regression with gaussian mixtures and partially-latent response variables
A simulated annealing version of the EM algorithm for non-Gaussian deconvolution
Spatial and non-spatial model-based protection procedures for the release of business microdata
Understanding predictive information criteria for Bayesian models
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems
Boosting flexible functional regression models with a high number of functional historical effects
Geographically Weighted Negative Binomial Regression - incorporating overdispersion
A fast and calibrated computer model emulator: an empirical Bayes approach
Nonconvex Dantzig selector and its parallel computing algorithm
Power enhancing probability subsampling using side information
Inferring multiple graphical structures
Efficient time/space algorithm to compute rectangular probabilities of multinomial, multivariate hypergeometric and multivariate Pólya distributions
Statistical modeling and analysis of high-resolution Synthetic Aperture Radar images
Snipping for robust k-means clustering under component-wise contamination
Sparse conformal predictors
An economical acceptance-rejection algorithm for uniform random variate generation over constrained simplexes
Data-driven stochastic inversion via functional quantization
Unbiased Bayesian inference for population Markov jump processes via random truncations
Erlang mixture modeling for Poisson process intensities
Ensemble sampler for infinite-dimensional inverse problems
Modeling with Mixtures of Linear Regressions
Personalized federated learning on large-scale association networks
Estimation of 2D jump location curve and 3D jump location surface in nonparametric regression
Automated statistical methods for measuring the strength of block ciphers
Testing for interactions in generalized additive models: Application to SO 2 pollution data
Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes
A note on a universal random variate generator for integer-valued random variables
A simulation approach to convergence rates for Markov chain Monte Carlo algorithms
Variational discriminant analysis with variable selection
Multivariate mixtures of normals with unknown number of components
Monte Carlo algorithms for computing α-permanents
D-optimal designs via a cocktail algorithm
Non-parametric bootstrap recycling
On the relative efficiency of a monotone parameter curve estimator in a functional nonlinear model
Constrained least squares simplicial-simplicial regression
Numerical Generalized Randomized HMC processes for restricted domains
KL-optimum designs: theoretical properties and practical computation
A semiparametric Bayesian approach to extreme value estimation
Consistent causal inference from time series with PC algorithm and its time-aware extension
On the shrinkage of local linear curve estimators
Classification using distance nearest neighbours
Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria
Learning binary undirected graph in low dimensional regime
A fast splitting procedure for classification trees
Copula directed acyclic graphs
A Bayesian decision theory approach to variable selection for discrimination
A global optimisation approach to range-restricted survey calibration
Efficient cross-validation of principal components applied to principal component regression
Bayesian point null hypothesis testing via the posterior likelihood ratio
Variational Bayes for estimating the parameters of a hidden Potts model
On the convergence of two sequential Monte Carlo methods for maximum a posteriori sequence estimation and stochastic global optimization
Rule-based Bayesian regression
Adaptive sequential design for regression on multi-resolution bases
Reduced-rank multi-label classification
Latent variable models with ordinal categorical covariates
Improved generalized Fourier amplitude sensitivity test (FAST) for model assessment
A parameter expansion version of the SAEM algorithm
A flexible statistical and efficient computational approach to object location applied to electrical tomography
Data free inference with processed data products
Beyond support in two-stage variable selection
An algorithm for the design of factorial experiments when the data are correlated
Iterated full partitions
Bayesian A-optimal two-phase designs with a single blocking factor in each phase
Learning from missing data with the binary latent block model
Implementation and analysis of GPU algorithms for Vecchia Approximation
Perfect simulation for Reed-Frost epidemic models
Generalized fused Lasso for grouped data in generalized linear models
Approximation of power in multivariate analysis
A registration-free approach for image monitoring
Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models
Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets
A focused information criterion for graphical models
Updating Variational Bayes: fast sequential posterior inference
Monotonic warpings for additive and deep Gaussian processes
Efficient simulated maximum likelihood with an application to online retailing
A wavelet-based approach for imputation in nonstationary multivariate time series
Sampling from compositional and directional distributions
Partially-latinized designs
Convergence rates of Gaussian ODE filters
Importance tempering
Twin Boosting: improved feature selection and prediction
Sequential changepoint detection in neural networks with checkpoints
Efficient computation of location depth contours by methods of computational geometry
Deep state-space Gaussian processes
The calibration of P-values, posterior Bayes factors and the AIC from the posterior distribution of the likelihood
Sparse reduced-rank regression with covariance estimation
Minimax optimal designs via particle swarm optimization methods
Estimation of spatial max-stable models using threshold exceedances
Bayesian ODE solvers: the maximum a posteriori estimate
A Bayesian method of distinguishing unit root from stationary processes based on panel data models with cross-sectional dependence
Sequential Monte Carlo methods for Bayesian elliptic inverse problems
Logit unfolding choice models for binary data
Bayesian inference for continuous-time hidden Markov models with an unknown number of states
Recursive inversion models for permutations
Filtering recursions for calculating likelihoods for queues based on inter-departure time data
Joint covariate selection and joint subspace selection for multiple classification problems
An empirical comparison of EM, SEM and MCMC performance for problematic Gaussian mixture likelihoods
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences
Expectile hidden Markov regression models for analyzing cryptocurrency returns
Bayesian quantile regression model with linear inequality constraints
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo
A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy
Permutation tests for between-unit fixed effects in multivariate generalized linear mixed models
INLA + : approximate Bayesian inference for non-sparse models using HPC
Efficient designs for constrained mixture experiments
Default risk prediction and feature extraction using a penalized deep neural network
Expected sample moments of concomitants of selected order statistics
Estimating time-varying directed neural networks
An adaptive-to-model test for partially parametric single-index models
On the grouped selection and model complexity of the adaptive elastic net
Bayesian shared parameter joint models for heterogeneous populations
Erratum to: Stability of noisy Metropolis-Hastings
Improving power posterior estimation of statistical evidence
Group inference for high-dimensional mediation models
Sparse optimal discriminant clustering
Function-on-function regression models with nonlinear dynamic effect and linear concurrent effect
A comment on the orthogonalization of B-spline basis functions and their derivatives
Continuity approximation in hybrid Bayesian networks structure learning
On-line changepoint detection and parameter estimation with application to genomic data
Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo
Uncertainty quantification and propagation in surrogate-based Bayesian inference
Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi's pseudodistance estimators
A distance-based diagnostic for trans-dimensional Markov chains
A joint kriging model with application to constrained classification
Zero-inflation in the multivariate poisson lognormal family
An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions
Variational inference for sparse spectrum Gaussian process regression
On bootstrapping the number of components in finite mixtures of Poisson distributions
Flexible pair-copula estimation in D-vines using bivariate penalized splines
Renewable composite quantile method and algorithm for nonparametric models with streaming data
Empirical likelihood for partially linear functional-coefficient autoregressive errors-in-variables models
Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks
Rank-based estimation for semiparametric accelerated failure time model under length-biased sampling
On the robustness of the generalized fused lasso to prior specifications
Properties of the stochastic approximation EM algorithm with mini-batch sampling
Expert-elicitation method for non-parametric joint priors using normalizing flows
A hybrid approach based on saddlepoint and importance sampling methods for bootstrap tail probability estimation
Robust variable selection in multiple functional linear models via group VIF regression
The FastHCS algorithm for robust PCA
Kullback-Leibler divergence based multidimensional robust universal hypothesis testing
Combinatorial EM algorithms
A novel Bayesian approach for latent variable modeling from mixed data with missing values
Computation for intrinsic variable selection in normal regression models via expected-posterior prior
A novel approach for parameter estimation of mixture of two Weibull distributions in failure data modeling
Real-time inference for smoothing quantile regression on streaming datasets with heterogeneity detection
Accelerated failure time models with error-prone response and nonlinear covariates
Variable selection for survival data with a class of adaptive elastic net techniques
Adaptation of the tuning parameter in general Bayesian inference with robust divergence
Adaptive Generalized P-Splines for Functional Data: A Statistical Framework via Blockwise GSVD
Variable selection and estimation for partially linear single-index models with longitudinal data
A discrepancy bound for deterministic acceptance-rejection samplers beyond N -1/2 in dimension 1
On Bayesian wavelet shrinkage estimation of nonparametric regression models with stationary correlated noise
Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes
Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models
Approximation of transition densities of stochastic differential equations by saddlepoint methods applied to small-time Ito-Taylor sample-path expansions
Computation of exact confidence intervals from discrete data using studentized test statistics
I-robust and D-robust designs on a finite design space
Bayesian parameter inference for partially observed stopped processes
Large-scale correlation screening under dependence for brain functional connectivity network inference
Self-healing umbrella sampling: convergence and efficiency
Statistics and computing: the genesis of data science
A new method for the estimation of variance matrix with prescribed zeros in nonlinear mixed effects models
A new maximum mean discrepancy based two-sample test for equal distributions in separable metric spaces
Generic reversible jump MCMC using graphical models
Improving bridge estimators via f-GAN
Variance reduction for additive functionals of Markov chains via martingale representations
Deep mixtures of unigrams for uncovering topics in textual data
Stochastic variational inference for large-scale discrete choice models using adaptive batch sizes
Real time anomaly detection and categorisation
Disclosure risk assessment in statistical microdata protection via advanced record linkage
Heterogeneity-aware debiased machine learning for high-dimensional partially linear models
Penalty Learning for Optimal Partitioning using Multilayer Perceptron
Asymptotic expansions of moments and cumulants
Computation of determinantal subset influence in regression
Preserving confidentiality of high-dimensional tabulated data: Statistical and computational issues
A permutation test for randomness with power against smooth variation
An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems
Evaluation of Tweedie exponential dispersion model densities by Fourier inversion
The second-derivative lower-bound function (SeLF) algorithm and three acceleration techniques for maximization with strongly stable convergence
Smooth expectiles for panel data using penalized splines
Shape modeling with spline partitions
Measuring non-linear dependence for two random variables distributed along a curve
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
Ensemble preconditioning for Markov chain Monte Carlo simulation
A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems
Profile empirical-likelihood inferences for the single-index-coefficient regression model
Semiparametric bivariate modelling with flexible extremal dependence
Nonparametric likelihood based estimation of linear filters for point processes
R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models
P-splines with derivative based penalties and tensor product smoothing of unevenly distributed data
Bayesian wavelet-packet historical functional linear models
Goodness-of-fit test of the mark distribution in a point process with non-stationary marks
Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution
Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models
Approximate Bayesian computational methods
Exact simulation of Gaussian Time Series from Nonparametric Spectral Estimates with Application to Bootstrapping
Randomized Spectral Clustering for Large-Scale Multi-Layer Networks
Semiparametric Bayesian analysis for longitudinal mixed effects models with non-normal AR(1) errors
Adaptive step-size selection for state-space probabilistic differential equation solvers
State-dependent swap strategies and automatic reduction of number of temperatures in adaptive parallel tempering algorithm
Likelihood-free approximate Gibbs sampling
Latent single-index models for ordinal data
The role of embedded integration rules in Bayesian statistics
An elliptically symmetric angular Gaussian distribution
Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method
Bayesian multivariate Poisson mixtures with an unknown number of components
Bayesian model comparison with un-normalised likelihoods
BAYES AND EMPIRICAL BAYES METHODS FOR DATA ANALYSIS
Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data
Calibrating the Gaussian multi-target tracking model
Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities
Image processing through multiscale analysis and measurement noise modeling
Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome
Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction
Globally and symmetrically identified Bayesian multinomial probit model
Efficient Shapley performance attribution for least-squares regression
Multiple Monte Carlo testing, with applications in spatial point processes
Block clustering with collapsed latent block models
Missing values: sparse inverse covariance estimation and an extension to sparse regression
Density estimation for toroidal data using semiparametric mixtures
Power-law distribution in pieces: a semi-parametric approach with change point detection
On proportional volume sampling for experimental design in general spaces
Bias-enhanced support detection and root finding approach
Statistical inference for matrix-vector linear regression without debiasing under Kronecker covariance structure
Noncrossing structured additive multiple-output Bayesian quantile regression models
Sampling based approach for one-hit and multi-hit models in quantal bioassay
A robust logistic discrimination model
euMMD: efficiently computing the MMD two-sample test statistic for univariate data
Anisotropic multidimensional smoothing using Bayesian tensor product P-splines
A robust model-based clustering based on the geometric median and the median covariation matrix
Stochastically optimal bootstrap sample size for shrinkage-type statistics
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling
Multilevel estimation of normalization constants using ensemble Kalman-Bucy filters
Ensemble Kalman inversion: mean-field limit and convergence analysis
Toeplitz Monte Carlo
Accelerating sequential Monte Carlo with surrogate likelihoods
Geographically weighted quantile regression for count Data
Complement to a comparative analysis of heuristics for the p -median problem
Multivariate Poisson regression with covariance structure
ABC Shadow algorithm: a tool for statistical analysis of spatial patterns
Spherical radial approximation for nested mixed effects models
Proximal Markov chain Monte Carlo algorithms
Latent variable techniques for categorical data
Local dimension reduction of summary statistics for likelihood-free inference
Methods for testing subblock patterns
Statistical inference and goodness-of-fit test in functional data via error distribution function
Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments
Jittering and clustering: strategies for the construction of robust designs
Maximum likelihood computation for fitting semiparametric mixture models
Deterministic approximate inference techniques for conditionally Gaussian state space models
Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models
A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance
Modularized Bayesian analyses and cutting feedback in likelihood-free inference
A reliable data-based smoothing parameter selection method for circular kernel estimation
Nonparametric additive location-scale models for interval censored data
A simple method for rejection sampling efficiency improvement on SIMT architectures
Riemann sums for MCMC estimation and convergence monitoring
On Bayesian analyses and finite mixtures for proportions
A modern retrospective on probabilistic numerics
Parallel algorithms for Markov chain Monte Carlo methods in latent spatial Gaussian models
Anisotropy of Hölder Gaussian random fields: characterization, estimation, and application to image textures
Optimal Monte Carlo integration on closed manifolds
Response improvement in complex experiments by co-information composite likelihood optimization
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences
Distance-based CUSUM statistics for high dimensional change points
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates
Robust wavelet shrinkage using robust selection of thresholds
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors
Optimal L 2 -norm empirical importance weights for the change of probability measure
Bayesian non-parametric modeling for integro-difference equations