Bayesian Inference

Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations NeurIPS 2010 Classification with Incomplete Data Using Dirichlet Process Priors JMLR 2010 Coherent Inference on Optimal Play in Game Trees AISTATS 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Construction of Dependent Dirichlet Processes based on Poisson Processes NeurIPS 2010 Content-based Image Retrieval with Multinomial Relevance Feedback ACML 2010 Copula Processes NeurIPS 2010 Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010 Dependent Indian Buffet Processes AISTATS 2010 Deterministic Bayesian inference for the $p*$ model AISTATS 2010 Deterministic Single-Pass Algorithm for LDA NeurIPS 2010 Dirichlet Process Mixtures of Generalized Linear Models AISTATS 2010 Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NeurIPS 2010 Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation ACML 2010 Efficient Multioutput Gaussian Processes through Variational Inducing Kernels AISTATS 2010 Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data RSS 2010 Elliptical slice sampling AISTATS 2010 Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Exact learning curves for Gaussian process regression on large random graphs NeurIPS 2010 Expectation Truncation and the Benefits of Preselection In Training Generative Models JMLR 2010 Extended Bayesian Information Criteria for Gaussian Graphical Models NeurIPS 2010 Focused Belief Propagation for Query-Specific Inference AISTATS 2010 Functional form of motion priors in human motion perception NeurIPS 2010 Gaussian Processes for Machine Learning (GPML) Toolbox JMLR 2010 Gaussian Process Preference Elicitation NeurIPS 2010