Bayesian Inference

Probabilistic Linear Multistep Methods NeurIPS 2016 Probabilistic Low-Rank Matrix Completion from Quantized Measurements JMLR 2016 Probing the Compositionality of Intuitive Functions NeurIPS 2016 Provable Bayesian Inference via Particle Mirror Descent AISTATS 2016 Pseudo-Marginal Slice Sampling AISTATS 2016 Reconstructing Parameters of Spreading Models from Partial Observations NeurIPS 2016 Recursive Decentralized Collaborative Localization for Sparsely Communicating Robots RSS 2016 Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks PGM 2016 Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016 Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks PGM 2016 Relevant sparse codes with variational information bottleneck NeurIPS 2016 Rényi Divergence Variational Inference NeurIPS 2016 Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics ICML 2016 Robust, Real-Time 3D Tracking of Multiple Objects With Similar Appearances CVPR 2016 Robust Sound Event Detection in Continuous Audio Environments Interspeech 2016 Sampling for Bayesian Program Learning NeurIPS 2016 Scalable Approximate Bayesian Inference for Outlier Detection under Informative Sampling JMLR 2016 Scalable Discrete Sampling as a Multi-Armed Bandit Problem ICML 2016 Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016 Scalable geometric density estimation AISTATS 2016 Scalable MAP inference in Bayesian networks based on a Map-Reduce approach PGM 2016 Scalable MCMC for Mixed Membership Stochastic Blockmodels AISTATS 2016 Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much NeurIPS 2016 Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models AISTATS 2016 Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues JMLR 2016