Bayesian Inference

Bayesian optimization for automated model selection NeurIPS 2016 Bayesian optimization for automated model selection AutoML 2016 Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models JMLR 2016 Bayesian Optimization for Probabilistic Programs NeurIPS 2016 Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach NeurIPS 2016 Bayesian Optimization with Robust Bayesian Neural Networks NeurIPS 2016 Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016 Bayesian Policy Gradient and Actor-Critic Algorithms JMLR 2016 Bayesian Torrent Classification by File Name and Size Only PGM 2016 Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies AISTATS 2016 Black-Box Alpha Divergence Minimization ICML 2016 Bootstrap-Based Regularization for Low-Rank Matrix Estimation JMLR 2016 C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching AISTATS 2016 Chained Gaussian Processes AISTATS 2016 Collapsed Variational Inference for Sum-Product Networks ICML 2016 Completely random measures for modelling block-structured sparse networks NeurIPS 2016 Compressed Gaussian Process for Manifold Regression JMLR 2016 Compressing Bayes Net CPTs with Persistent Leaky Causes PGM 2016 Computational Imaging for VLBI Image Reconstruction CVPR 2016 Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016 Conditional Generative Moment-Matching Networks NeurIPS 2016 Conditional Graphical Lasso for Multi-Label Image Classification CVPR 2016 Consistency and Fluctuations For Stochastic Gradient Langevin Dynamics JMLR 2016 Coresets for Scalable Bayesian Logistic Regression NeurIPS 2016 CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data JMLR 2016