Bayesian & Probabilistic

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models NeurIPS 2006 Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing NeurIPS 2006 Using Combinatorial Optimization within Max-Product Belief Propagation NeurIPS 2006 Walk-Sums and Belief Propagation in Gaussian Graphical Models JMLR 2006 A Unifying View of Sparse Approximate Gaussian Process Regression JMLR 2005 Expectation Consistent Approximate Inference JMLR 2005 Inner Product Spaces for Bayesian Networks JMLR 2005 Interacting Markov Random Fields for Simultaneous Terrain Modeling and Obstacle Detection RSS 2005 Learning Module Networks JMLR 2005 Local Propagation in Conditional Gaussian Bayesian Networks JMLR 2005 Loopy Belief Propagation: Convergence and Effects of Message Errors JMLR 2005 Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005 What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks JMLR 2005 Exact Bayesian Structure Discovery in Bayesian Networks JMLR 2004 Hierarchical Latent Class Models for Cluster Analysis JMLR 2004 Large-Sample Learning of Bayesian Networks is NP-Hard JMLR 2004 Probability Product Kernels JMLR 2004 Combining Knowledge from Different Sources in Causal Probabilistic Models JMLR 2003 Energy-Based Models for Sparse Overcomplete Representations JMLR 2003 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains JMLR 2003 Learning Probabilistic Models: An Expected Utility Maximization Approach JMLR 2003 On Inclusion-Driven Learning of Bayesian Networks JMLR 2003 Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet JMLR 2003 Task Clustering and Gating for Bayesian Multitask Learning JMLR 2003 Learning Equivalence Classes of Bayesian-Network Structures JMLR 2002