Bayesian & Probabilistic

Variational Gaussian Copula Inference AISTATS 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features Interspeech 2016 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Active Learning for Structured Probabilistic Models With Histogram Approximation CVPR 2015 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A Gaussian Process Model of Quasar Spectral Energy Distributions NeurIPS 2015 A Hybrid Approach for Probabilistic Inference using Random Projections ICML 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 A Multitask Point Process Predictive Model ICML 2015 An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process ICML 2015 A New Perspective and Extension of the Gaussian Filter RSS 2015 A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis ICCV 2015 A Spectral Algorithm for Inference in Hidden semi-Markov Models AISTATS 2015 Associative Memory via a Sparse Recovery Model NeurIPS 2015 Atomic Spatial Processes ICML 2015 A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding NeurIPS 2015 A trust-region method for stochastic variational inference with applications to streaming data ICML 2015 A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data ICML 2015 Automatic Variational Inference in Stan NeurIPS 2015 Barrier Frank-Wolfe for Marginal Inference NeurIPS 2015 Bayesian and Empirical Bayesian Forests ICML 2015 Bayesian dark knowledge NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NeurIPS 2015