posterior distribution

Robust and Scalable Bayes via a Median of Subset Posterior Measures JMLR 2017 Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness AISTATS 2017 Stochastic Gradient Monomial Gamma Sampler ICML 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 Causal Inference through a Witness Protection Program JMLR 2016 Compressed Gaussian Process for Manifold Regression JMLR 2016 Determinantal Regularization for Ensemble Variable Selection AISTATS 2016 DISCO Nets : DISsimilarity COefficients Networks NeurIPS 2016 Early Stopping as Nonparametric Variational Inference AISTATS 2016 Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation NeurIPS 2016 Interactive Bayesian Hierarchical Clustering ICML 2016 Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease PGM 2016 Learning Parameters of Hybrid Time Bayesian Networks PGM 2016 MCMC Shape Sampling for Image Segmentation With Nonparametric Shape Priors CVPR 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Sampling for Bayesian Program Learning NeurIPS 2016 Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016 Bayesian Multiple Target Localization ICML 2015 Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields AISTATS 2015 Finite-Time Analysis of Projected Langevin Monte Carlo NeurIPS 2015 Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior JMLR 2015 Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference NeurIPS 2015 Stochastic Structured Variational Inference AISTATS 2015 Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring NeurIPS 2015 Variational Inference with Normalizing Flows ICML 2015