Models

Probabilistic Principal Geodesic Analysis NeurIPS 2013 Relevance Topic Model for Unstructured Social Group Activity Recognition NeurIPS 2013 Restoring an Image Taken through a Window Covered with Dirt or Rain ICCV 2013 RNADE: The real-valued neural autoregressive density-estimator NeurIPS 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Stochastic Variational Inference JMLR 2013 Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013 Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions AISTATS 2013 Training and Analysing Deep Recurrent Neural Networks NeurIPS 2013 Understanding High-Level Semantics by Modeling Traffic Patterns ICCV 2013 Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines CVPR 2013 A Better Way to Pretrain Deep Boltzmann Machines NeurIPS 2012 Affine Independent Variational Inference NeurIPS 2012 A Generative Model for Parts-based Object Segmentation NeurIPS 2012 A Neural Autoregressive Topic Model NeurIPS 2012 A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012 Bayesian Probabilistic Co-Subspace Addition NeurIPS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Cardinality Restricted Boltzmann Machines NeurIPS 2012 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis ACML 2012 Deep Boltzmann Machines as Feed-Forward Hierarchies AISTATS 2012 Discriminative Learning of Sum-Product Networks NeurIPS 2012 Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression NeurIPS 2012 Hierarchical spike coding of sound NeurIPS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012