Probabilistic Modeling

The Noisy-Logical Distribution and its Application to Causal Inference NeurIPS 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 A Linear Non-Gaussian Acyclic Model for Causal Discovery JMLR 2006 Analysis of Contour Motions NeurIPS 2006 An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NeurIPS 2006 Approximate inference using planar graph decomposition NeurIPS 2006 A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data NeurIPS 2006 A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests JMLR 2006 A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo NeurIPS 2006 Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure NeurIPS 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Bayesian Network Learning with Parameter Constraints JMLR 2006 Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation JMLR 2006 Clustering Under Prior Knowledge with Application to Image Segmentation NeurIPS 2006 Conditional mean field NeurIPS 2006 Context Effects in Category Learning: An Investigation of Four Probabilistic Models NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors NeurIPS 2006 Detecting Humans via Their Pose NeurIPS 2006 Differential Entropic Clustering of Multivariate Gaussians NeurIPS 2006