Bayesian Inference

Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016 Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks PGM 2016 Scalable Discrete Sampling as a Multi-Armed Bandit Problem ICML 2016 Scalable MAP inference in Bayesian networks based on a Map-Reduce approach PGM 2016 Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays ACML 2016 Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NeurIPS 2016 Synthesis of MCMC and Belief Propagation NeurIPS 2016 The Parameterized Complexity of Approximate Inference in Bayesian Networks PGM 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A Gaussian Process Model of Quasar Spectral Energy Distributions NeurIPS 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding NeurIPS 2015 Automatic Variational Inference in Stan NeurIPS 2015 Bayesian dark knowledge NeurIPS 2015 Biologically Inspired Dynamic Textures for Probing Motion Perception NeurIPS 2015 Bounding errors of Expectation-Propagation NeurIPS 2015 Bounding the Cost of Search-Based Lifted Inference NeurIPS 2015 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NeurIPS 2015 Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NeurIPS 2015 Expectation Particle Belief Propagation NeurIPS 2015 Fast Lifted MAP Inference via Partitioning NeurIPS 2015