Bayesian & Probabilistic

Dynamic Copula Networks for Modeling Real-valued Time Series AISTATS 2013 Dynamic Probabilistic Volumetric Models ICCV 2013 Dynamic Scaled Sampling for Deterministic Constraints 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 Optimization for Sparse Gaussian Process Regression NeurIPS 2013 Efficient Variational Inference for Gaussian Process Regression Networks AISTATS 2013 Embed and Project: Discrete Sampling with Universal Hashing NeurIPS 2013 Evidence Estimation for Bayesian Partially Observed MRFs AISTATS 2013 Exact Learning of Bounded Tree-width Bayesian Networks AISTATS 2013 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Fast Determinantal Point Process Sampling with Application to Clustering NeurIPS 2013 Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models ICML 2013 Fast Near-GRID Gaussian Process Regression AISTATS 2013 Fingerspelling Recognition with Semi-Markov Conditional Random Fields ICCV 2013 First-order Decomposition Trees NeurIPS 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting NeurIPS 2013 Fully-Connected CRFs with Non-Parametric Pairwise Potential CVPR 2013 Gaussian Process Conditional Copulas with Applications to Financial Time Series NeurIPS 2013 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 Generalized Denoising Auto-Encoders as Generative Models NeurIPS 2013 Generalized Method-of-Moments for Rank Aggregation NeurIPS 2013