Variational Inference

Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms NeurIPS 2013 Smooth Operators ICML 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Streaming Variational Bayes NeurIPS 2013 Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013 Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression NeurIPS 2013 Variational Planning for Graph-based MDPs NeurIPS 2013 Affine Independent Variational Inference NeurIPS 2012 Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks AISTATS 2012 A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012 Bayesian Pedigree Analysis using Measure Factorization NeurIPS 2012 Bayesian Probabilistic Co-Subspace Addition NeurIPS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models NeurIPS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Density Propagation and Improved Bounds on the Partition Function NeurIPS 2012 Dual-Space Analysis of the Sparse Linear Model NeurIPS 2012 Expectation Propagation in Gaussian Process Dynamical Systems NeurIPS 2012 Factorized Asymptotic Bayesian Inference for Mixture Modeling AISTATS 2012 Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression NeurIPS 2012 Fast Variational Bayesian Inference for Non-Conjugate Matrix Factorization Models AISTATS 2012 Fast Variational Inference in the Conjugate Exponential Family NeurIPS 2012 Fast Variational Mode-Seeking AISTATS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012