Models

Generative Local Metric Learning for Nearest Neighbor Classification NeurIPS 2010 Global Analytic Solution for Variational Bayesian Matrix Factorization NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model NeurIPS 2010 Improving posterior marginal approximations in latent Gaussian models AISTATS 2010 Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010 Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development NeurIPS 2010 Learning to combine foveal glimpses with a third-order Boltzmann machine NeurIPS 2010 Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010 Regularized estimation of image statistics by Score Matching NeurIPS 2010 Structured Determinantal Point Processes NeurIPS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 Variational bounds for mixed-data factor analysis NeurIPS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 3D Object Recognition with Deep Belief Nets NeurIPS 2009 A Gaussian Tree Approximation for Integer Least-Squares NeurIPS 2009 A Stochastic approximation method for inference in probabilistic graphical models NeurIPS 2009 Evaluating multi-class learning strategies in a generative hierarchical framework for object detection NeurIPS 2009 Free energy score space NeurIPS 2009 Learning a Small Mixture of Trees NeurIPS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009 Posterior vs Parameter Sparsity in Latent Variable Models NeurIPS 2009 Replicated Softmax: an Undirected Topic Model NeurIPS 2009