Probabilistic Modeling

Linear Programs for Hypotheses Selection in Probabilistic Inference Models JMLR 2006 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model NeurIPS 2006 Multi-dynamic Bayesian Networks NeurIPS 2006 Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints NeurIPS 2006 Noisy-OR Component Analysis and its Application to Link Analysis JMLR 2006 Non-rigid point set registration: Coherent Point Drift NeurIPS 2006 Probabilistic Terrain Analysis For High-Speed Desert Driving RSS 2006 Relational Learning with Gaussian Processes NeurIPS 2006 Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006 Statistical Modeling of Images with Fields of Gaussian Scale Mixtures NeurIPS 2006 Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NeurIPS 2006 Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks NeurIPS 2006 Temporal Coding using the Response Properties of Spiking Neurons NeurIPS 2006 The Neurodynamics of Belief Propagation on Binary Markov Random Fields NeurIPS 2006 Training Conditional Random Fields for Maximum Labelwise Accuracy 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 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