Bayesian & Probabilistic

Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data NeurIPS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Learning models of object structure NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Localizing Bugs in Program Executions with Graphical Models NeurIPS 2009 Local Rules for Global MAP: When Do They Work ? NeurIPS 2009 Maximum likelihood trajectories for continuous-time Markov chains NeurIPS 2009 Modeling Social Annotation Data with Content Relevance using a Topic Model NeurIPS 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Nonlinear directed acyclic structure learning with weakly additive noise models NeurIPS 2009 Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations NeurIPS 2009 Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution NeurIPS 2009 Nonparametric Bayesian Texture Learning and Synthesis NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009 Non-stationary continuous dynamic Bayesian networks NeurIPS 2009 Occlusive Components Analysis NeurIPS 2009 Optimal context separation of spiking haptic signals by second-order somatosensory neurons NeurIPS 2009 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009 Perceptual Multistability as Markov Chain Monte Carlo Inference NeurIPS 2009 Posterior vs Parameter Sparsity in Latent Variable Models NeurIPS 2009 Probabilistic Relational PCA NeurIPS 2009