Bayesian & Probabilistic

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 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NeurIPS 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Part-based Probabilistic Point Matching using Equivalence Constraints NeurIPS 2006 Particle Filtering for Nonparametric Bayesian Matrix Factorization NeurIPS 2006 Recursive Attribute Factoring NeurIPS 2006 Relational Learning with Gaussian Processes NeurIPS 2006 Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006 Simplifying Mixture Models through Function Approximation NeurIPS 2006 Single Channel Speech Separation Using Factorial Dynamics NeurIPS 2006 Statistical Modeling of Images with Fields of Gaussian Scale Mixtures NeurIPS 2006 Stochastic Relational Models for Discriminative Link Prediction 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 The Neurodynamics of Belief Propagation on Binary Markov Random Fields NeurIPS 2006 Tighter PAC-Bayes Bounds NeurIPS 2006 Towards a general independent subspace analysis NeurIPS 2006 Training Conditional Random Fields for Maximum Labelwise Accuracy NeurIPS 2006 Uncertainty, phase and oscillatory hippocampal recall NeurIPS 2006 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