Bayesian Learning

Sequential Inference for Deep Gaussian Process AISTATS 2016 Stability of Controllers for Gaussian Process Forward Models ICML 2016 Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016 Student Skill Models in Adaptive Testing PGM 2016 The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes JMLR 2016 The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks ICML 2016 The Nonparametric Kernel Bayes Smoother AISTATS 2016 Unbounded Bayesian Optimization via Regularization AISTATS 2016 Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NeurIPS 2016 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process ICML 2015 A New Perspective and Extension of the Gaussian Filter RSS 2015 A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis ICCV 2015 Atomic Spatial Processes ICML 2015 A trust-region method for stochastic variational inference with applications to streaming data ICML 2015 Bayesian and Empirical Bayesian Forests ICML 2015 Bayesian Multiple Target Localization ICML 2015 Bayesian Nonparametric Covariance Regression JMLR 2015 Bayesian Nonparametric Crowdsourcing JMLR 2015 Bayesian Non-Parametric Inference for Manifold Based MoCap Representation ICCV 2015 Bayesian Optimization with Exponential Convergence NeurIPS 2015 Concave Penalized Estimation of Sparse Gaussian Bayesian Networks JMLR 2015 Controversy in mechanistic modelling with Gaussian processes ICML 2015