mixture model

DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data CVPR 2017 Event extraction from Twitter using Non-Parametric Bayesian Mixture Model with Word Embeddings EACL 2017 Infinite Variational Autoencoder for Semi-Supervised Learning CVPR 2017 Noisy Population Recovery from Unknown Noise COLT 2017 Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models JMLR 2017 Variational Boosting: Iteratively Refining Posterior Approximations ICML 2017 Variational Mixtures of Gaussian Processes for Classification IJCAI 2017 A Locally Adaptive Normal Distribution NeurIPS 2016 CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data JMLR 2016 Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data ICML 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NeurIPS 2016 Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016 Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs COLING 2016 Learning Mixtures of Plackett-Luce Models ICML 2016 Online Trans-dimensional von Mises-Fisher Mixture Models for User Profiles JMLR 2016 On Mixtures of Markov Chains NeurIPS 2016 Provable Tensor Methods for Learning Mixtures of Generalized Linear Models AISTATS 2016 Robust, Real-Time 3D Tracking of Multiple Objects With Similar Appearances CVPR 2016 Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures AISTATS 2016 The Power of Adaptivity in Identifying Statistical Alternatives NeurIPS 2016 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A Dirichlet Process Mixture Model for Spherical Data AISTATS 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 Automatic Variational Inference in Stan NeurIPS 2015 Class-prior Estimation for Learning from Positive and Unlabeled Data ACML 2015