variational inference

Decoupled Variational Gaussian Inference NeurIPS 2014 Deep AutoRegressive Networks ICML 2014 Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes ICML 2014 Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models NeurIPS 2014 Dual online inference for latent Dirichlet allocation ACML 2014 Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014 Efficient Inference for Complex Queries on Complex Distributions AISTATS 2014 Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NeurIPS 2014 Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables AISTATS 2014 Extended and Unscented Gaussian Processes NeurIPS 2014 Fast Allocation of Gaussian Process Experts ICML 2014 From MAP to Marginals: Variational Inference in Bayesian Submodular Models NeurIPS 2014 Hierarchical Dirichlet Scaling Process ICML 2014 Iterative Neural Autoregressive Distribution Estimator NADE-k NeurIPS 2014 Making Pairwise Binary Graphical Models Attractive NeurIPS 2014 Neural Variational Inference and Learning in Belief Networks ICML 2014 On Prior Distributions and Approximate Inference for Structured Variables NeurIPS 2014 Projecting Markov Random Field Parameters for Fast Mixing NeurIPS 2014 Robust Bayesian Max-Margin Clustering NeurIPS 2014 Robust Principal Component Analysis with Complex Noise ICML 2014 Scalable Variational Bayesian Matrix Factorization with Side Information AISTATS 2014 Semi-supervised Learning with Deep Generative Models NeurIPS 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Sparse meta-Gaussian information bottleneck ICML 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014