Variational Inference

Learning Structured Output Representation using Deep Conditional Generative Models NeurIPS 2015 Learning Wake-Sleep Recurrent Attention Models NeurIPS 2015 On some provably correct cases of variational inference for topic models NeurIPS 2015 Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NeurIPS 2015 Stochastic Expectation Propagation NeurIPS 2015 The Population Posterior and Bayesian Modeling on Streams NeurIPS 2015 Variational Dropout and the Local Reparameterization Trick NeurIPS 2015 Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning NeurIPS 2015 A Bayesian model for identifying hierarchically organised states in neural population activity NeurIPS 2014 A Complete Variational Tracker NeurIPS 2014 Analysis of Brain States from Multi-Region LFP Time-Series NeurIPS 2014 Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NeurIPS 2014 Automated Variational Inference for Gaussian Process Models NeurIPS 2014 Clamping Variables and Approximate Inference NeurIPS 2014 Decoupled Variational Gaussian Inference NeurIPS 2014 Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NeurIPS 2014 Extended and Unscented Gaussian Processes NeurIPS 2014 From MAP to Marginals: Variational Inference in Bayesian Submodular Models NeurIPS 2014 Iterative Neural Autoregressive Distribution Estimator NADE-k NeurIPS 2014 Smoothed Gradients for Stochastic Variational Inference NeurIPS 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NeurIPS 2013 Demixing odors - fast inference in olfaction NeurIPS 2013 Integrated Non-Factorized Variational Inference NeurIPS 2013