Probabilistic Modeling

Relational Dependency Networks JMLR 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Spatial Latent Dirichlet Allocation NeurIPS 2007 The Noisy-Logical Distribution and its Application to Causal Inference NeurIPS 2007 The rat as particle filter NeurIPS 2007 The Value of Labeled and Unlabeled Examples when the Model is Imperfect NeurIPS 2007 Truncating the Loop Series Expansion for Belief Propagation JMLR 2007 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models 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 Probabilistic Exemplar Approach to Combine Laser and Vision for Person Tracking RSS 2006 A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo NeurIPS 2006 Context Effects in Category Learning: An Investigation of Four Probabilistic Models NeurIPS 2006 Detecting Humans via Their Pose NeurIPS 2006 Distributed Inference in Dynamical Systems NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006 Generalized Bradley-Terry Models and Multi-Class Probability Estimates JMLR 2006 Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space NeurIPS 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006 Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models NeurIPS 2006 Linear Programming Relaxations and Belief Propagation -- An Empirical Study JMLR 2006