Bayesian & Probabilistic

Exact Inference on Gaussian Graphical Models of Arbitrary Topology using Path-Sums JMLR 2016 Examples are not enough, learn to criticize! Criticism for Interpretability NeurIPS 2016 Exponential Family Embeddings NeurIPS 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NeurIPS 2016 Flexible Models for Microclustering with Application to Entity Resolution NeurIPS 2016 Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NeurIPS 2016 Gaussian Processes for Survival Analysis NeurIPS 2016 Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain NeurIPS 2016 Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables AISTATS 2016 Globally Sparse Probabilistic PCA AISTATS 2016 Hawkes Processes with Stochastic Excitations ICML 2016 Herded Gibbs Sampling JMLR 2016 Hierarchical Compound Poisson Factorization ICML 2016 HMM-Based Non-Native Accent Assessment Using Posterior Features Interspeech 2016 Hybrid Copula Bayesian Networks PGM 2016 Identifying the irreducible disjoint factors of a multivariate probability distribution PGM 2016 Improving Structure MCMC for Bayesian Networks through Markov Blanket Resampling JMLR 2016 Incremental Variational Sparse Gaussian Process Regression NeurIPS 2016 Inference by Reparameterization in Neural Population Codes NeurIPS 2016 Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016 Interactive Bayesian Hierarchical Clustering ICML 2016 Isotonic Hawkes Processes ICML 2016 Iterative Refinement of the Approximate Posterior for Directed Belief Networks NeurIPS 2016 Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease PGM 2016 Joint Structural Estimation of Multiple Graphical Models JMLR 2016