Bayesian Inference

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 Hierarchical Gaussian Process Regression ACML 2010 Implicit Differentiation by Perturbation NeurIPS 2010 Implicit encoding of prior probabilities in optimal neural populations NeurIPS 2010 Improvements to the Sequence Memoizer NeurIPS 2010 Improving posterior marginal approximations in latent Gaussian models AISTATS 2010 Incremental Sigmoid Belief Networks for Grammar Learning JMLR 2010 Inducing Tree-Substitution Grammars JMLR 2010 Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Infinite Predictor Subspace Models for Multitask Learning AISTATS 2010 Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks 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 Bayesian Network Structure using LP Relaxations AISTATS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 Learning Instance-Specific Predictive Models JMLR 2010 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Learning the Structure of Deep Sparse Graphical Models AISTATS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 Mass Fatality Incident Identification based on nuclear DNA evidence AISTATS 2010