bayesian inference

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 probabilistic planar robot motion estimation given pairs of images RSS 2010 Elliptical slice sampling AISTATS 2010 Exact learning curves for Gaussian process regression on large random graphs NeurIPS 2010 Functional form of motion priors in human motion perception NeurIPS 2010 Gaussian Process Preference Elicitation NeurIPS 2010 Gaussian sampling by local perturbations NeurIPS 2010 Global Analytic Solution for Variational Bayesian Matrix Factorization NeurIPS 2010 Global seismic monitoring as probabilistic inference NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Heavy-Tailed Process Priors for Selective Shrinkage NeurIPS 2010 Image Denoising with Kernels Based on Natural Image Relations JMLR 2010 Improvements to the Sequence Memoizer NeurIPS 2010 Improving posterior marginal approximations in latent Gaussian models AISTATS 2010 Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents NeurIPS 2010 Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development NeurIPS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010