Bayesian Inference

Discrete MRF Inference of Marginal Densities for Non-uniformly Discretized Variable Space CVPR 2013 Discriminative Brain Effective Connectivity Analysis for Alzheimer's Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network CVPR 2013 Discriminative Transfer Learning with Tree-based Priors NeurIPS 2013 Distributed and Adaptive Darting Monte Carlo through Regenerations AISTATS 2013 Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods AISTATS 2013 Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture NeurIPS 2013 Dynamic Copula Networks for Modeling Real-valued Time Series AISTATS 2013 EDML for Learning Parameters in Directed and Undirected Graphical Models NeurIPS 2013 Efficiently Sampling Probabilistic Programs via Program Analysis AISTATS 2013 Efficient Online Inference for Bayesian Nonparametric Relational Models NeurIPS 2013 Efficient Variational Inference for Gaussian Process Regression Networks AISTATS 2013 Evidence Estimation for Bayesian Partially Observed MRFs AISTATS 2013 Exact Learning of Bounded Tree-width Bayesian Networks AISTATS 2013 Expensive Function Optimization with Stochastic Binary Outcomes ICML 2013 Exploring the Mind: Integrating Questionnaires and fMRI ICML 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models ICML 2013 Fast Max-Margin Matrix Factorization with Data Augmentation ICML 2013 Fast MCMC Sampling for Markov Jump Processes and Extensions JMLR 2013 Fast Near-GRID Gaussian Process Regression AISTATS 2013 Fast Probabilistic Optimization from Noisy Gradients ICML 2013 Finding Optimal Bayesian Networks Using Precedence Constraints JMLR 2013 First-order Decomposition Trees NeurIPS 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Further Optimal Regret Bounds for Thompson Sampling AISTATS 2013