| Publication | Date of Publication | Type |
|---|
| A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters | 2023-10-09 | Paper |
| Identification of factors impacting on the transmission and mortality of COVID-19 | 2023-09-27 | Paper |
| Consistent Sparse Deep Learning: Theory and Computation | 2023-07-06 | Paper |
| Markov Neighborhood Regression for High-Dimensional Inference | 2023-03-09 | Paper |
| Nearly optimal Bayesian shrinkage for high-dimensional regression | 2023-02-03 | Paper |
| A Kernel-Expanded Stochastic Neural Network | 2022-09-27 | Paper |
| An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization | 2022-08-01 | Paper |
| Stochastic gradient Langevin dynamics with adaptive drifts | 2022-03-24 | Paper |
| Stochastic approximation Hamiltonian Monte Carlo | 2022-02-23 | Paper |
| Learning sparse deep neural networks with a spike-and-slab prior | 2021-11-12 | Paper |
| Learning Moral Graphs in Construction of High-Dimensional Bayesian Networks for Mixed Data | 2021-10-01 | Paper |
| Extended stochastic gradient Markov chain Monte Carlo for large-scale Bayesian variable selection | 2021-01-21 | Paper |
| Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction | 2020-10-02 | Paper |
| Non-convex Learning via Replica Exchange Stochastic Gradient MCMC | 2020-08-12 | Paper |
| A Bayesian mark interaction model for analysis of tumor pathology images | 2019-12-19 | Paper |
| Double-parallel Monte Carlo for Bayesian analysis of big data | 2019-10-18 | Paper |
| https://portal.mardi4nfdi.de/entity/Q5224397 | 2019-07-23 | Paper |
| Accelerate training of restricted Boltzmann machines via iterative conditional maximum likelihood estimation | 2019-06-27 | Paper |
| A Split-and-Merge Bayesian Variable Selection Approach for Ultrahigh Dimensional Regression | 2019-06-12 | Paper |
| A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants | 2019-06-12 | Paper |
| An Imputation–Regularized Optimization Algorithm for High Dimensional Missing Data Problems and Beyond | 2019-03-06 | Paper |
| Bayesian Neural Networks for Selection of Drug Sensitive Genes | 2018-12-04 | Paper |
| Learning gene regulatory networks from next generation sequencing data | 2018-11-16 | Paper |
| Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants | 2018-11-08 | Paper |
| A Bayesian generalized linear model for Crimean-Congo hemorrhagic fever incidents | 2018-08-08 | Paper |
| A split-and-merge approach for singular value decomposition of large-scale matrices | 2018-05-08 | Paper |
| Parallel and interacting stochastic approximation annealing algorithms for global optimisation | 2018-03-07 | Paper |
| Nearly optimal Bayesian Shrinkage for High Dimensional Regression | 2017-12-24 | Paper |
| An Equivalent Measure of Partial Correlation Coefficients for High-Dimensional Gaussian Graphical Models | 2017-10-13 | Paper |
| High-Dimensional Variable Selection With Reciprocal L1-Regularization | 2017-10-13 | Paper |
| Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule | 2017-08-04 | Paper |
| Bayesian analysis for exponential random graph models using the adaptive exchange sampler | 2015-12-10 | Paper |
| Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities | 2015-11-12 | Paper |
| A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets | 2015-10-21 | Paper |
| Weak Convergence Rates of Population Versus Single-Chain Stochastic Approximation MCMC Algorithms | 2015-01-19 | Paper |
| Bayesian Subset Modeling for High-Dimensional Generalized Linear Models | 2013-08-07 | Paper |
| Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter | 2013-04-26 | Paper |
| A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data | 2013-04-26 | Paper |
| Intrinsic Regression Models for Medial Representation of Subcortical Structures | 2013-04-22 | Paper |
| Annealing evolutionary stochastic approximation Monte Carlo for global optimization | 2013-01-16 | Paper |
| Annealing evolutionary stochastic approximation Monte Carlo for global optimization | 2012-12-31 | Paper |
| Efficient p-value evaluation for resampling-based tests | 2011-07-27 | Paper |
| A double Metropolis–Hastings sampler for spatial models with intractable normalizing constants | 2011-07-06 | Paper |
| Robust Clustering Using Exponential Power Mixtures | 2011-02-17 | Paper |
| Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model | 2011-02-17 | Paper |
| Trajectory averaging for stochastic approximation MCMC algorithms | 2010-11-15 | Paper |
| https://portal.mardi4nfdi.de/entity/Q3056193 | 2010-11-10 | Paper |
| Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo | 2010-10-01 | Paper |
| Advanced Markov Chain Monte Carlo Methods | 2010-07-09 | Paper |
| Learning Bayesian networks for discrete data | 2010-03-30 | Paper |
| Estimating the false discovery rate using the stochastic approximation algorithm | 2009-09-30 | Paper |
| Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems | 2009-08-19 | Paper |
| Use of SVD-based probit transformation in clustering gene expression profiles | 2009-06-02 | Paper |
| On the use of stochastic approximation Monte Carlo for Monte Carlo integration | 2009-03-20 | Paper |
| https://portal.mardi4nfdi.de/entity/Q3543632 | 2008-12-04 | Paper |
| Efficient MCMC estimation of discrete distributions | 2008-11-26 | Paper |
| Convergence of stochastic approximation algorithms under irregular conditions | 2008-09-18 | Paper |
| https://portal.mardi4nfdi.de/entity/Q5434038 | 2008-01-09 | Paper |
| Annealing stochastic approximation Monte Carlo algorithm for neural network training | 2007-09-20 | Paper |
| Stochastic Approximation in Monte Carlo Computation | 2007-09-18 | Paper |
| A Generalized Wang–Landau Algorithm for Monte Carlo Computation | 2007-08-20 | Paper |
| A theory on flat histogram Monte Carlo algorithms | 2006-06-14 | Paper |
| Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo | 2005-05-23 | Paper |
| An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine | 2004-09-07 | Paper |
| Dynamically Weighted Importance Sampling in Monte Carlo Computation | 2004-06-10 | Paper |
| A Theory for Dynamic Weighting in Monte Carlo Computation | 2003-08-13 | Paper |
| Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models | 2003-08-13 | Paper |
| Some connections between Bayesian and non-Bayesian methods for regression model selection | 2002-09-05 | Paper |
| The Multiple-Try Method and Local Optimization in Metropolis Sampling | 2002-07-30 | Paper |
| https://portal.mardi4nfdi.de/entity/Q2770355 | 2002-05-13 | Paper |
| https://portal.mardi4nfdi.de/entity/Q4488839 | 2000-01-01 | Paper |
| Dynamic weighting in Monte Carlo and optimization | 1998-11-03 | Paper |
