probabilistic graphical model

Copula Bayesian Networks NeurIPS 2010 Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NeurIPS 2010 Efficient Relational Learning with Hidden Variable Detection NeurIPS 2010 Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Focused Belief Propagation for Query-Specific Inference AISTATS 2010 Inference and Learning in Networks of Queues AISTATS 2010 Layered image motion with explicit occlusions, temporal consistency, and depth ordering NeurIPS 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Why are DBNs sparse? AISTATS 2010 An LP View of the M-best MAP problem NeurIPS 2009 Approximating MAP by Compensating for Structural Relaxations NeurIPS 2009 A Stochastic approximation method for inference in probabilistic graphical models NeurIPS 2009 Conditional Neural Fields NeurIPS 2009 Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora NeurIPS 2009 Sparsistent Learning of Varying-coefficient Models with Structural Changes NeurIPS 2009 Gates NeurIPS 2008 Efficient Principled Learning of Thin Junction Trees NeurIPS 2007 Infinite State Bayes-Nets for Structured Domains NeurIPS 2007 Spatial Latent Dirichlet Allocation NeurIPS 2007 A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data NeurIPS 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Multi-dynamic Bayesian Networks NeurIPS 2006 Training Conditional Random Fields for Maximum Labelwise Accuracy NeurIPS 2006