Bayesian & Probabilistic

Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks NeurIPS 2018 On Nesting Monte Carlo Estimators ICML 2018 On Robust Trimming of Bayesian Network Classifiers IJCAI 2018 On Semiparametric Exponential Family Graphical Models JMLR 2018 On Statistical Optimality of Variational Bayes AISTATS 2018 On the challenges of learning with inference networks on sparse, high-dimensional data AISTATS 2018 On the Relative Expressiveness of Bayesian and Neural Networks PGM 2018 Optimistic optimization of a Brownian NeurIPS 2018 Optimization, fast and slow: optimally switching between local and Bayesian optimization ICML 2018 Overlapping Clustering Models, and One (class) SVM to Bind Them All NeurIPS 2018 Parallel Probabilistic Inference by Weighted Model Counting PGM 2018 Parameterised Queries and Lifted Query Answering IJCAI 2018 Patchwork Kriging for Large-scale Gaussian Process Regression JMLR 2018 PhraseCTM: Correlated Topic Modeling on Phrases within Markov Random Fields ACL 2018 Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis NeurIPS 2018 Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018 Power-law efficient neural codes provide general link between perceptual bias and discriminability NeurIPS 2018 Principled Selection of Hyperparameters in the Latent Dirichlet Allocation Model JMLR 2018 Probabilistic Boolean Tensor Decomposition ICML 2018 Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures ACL 2018 Probabilistic Joint Face-Skull Modelling for Facial Reconstruction CVPR 2018 Probabilistic Matrix Factorization for Automated Machine Learning NeurIPS 2018 Probabilistic Model-Agnostic Meta-Learning NeurIPS 2018 Probabilistic Plant Modeling via Multi-View Image-to-Image Translation CVPR 2018 Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks PGM 2018