bayesian nonparametric model

HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery UAI 2025 Bayesian Adaptive Superpixel Segmentation ICCV 2019 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018 Clustering Induced Kernel Learning ACML 2018 Bayesian Learning of Dynamic Multilayer Networks JMLR 2017 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models ICML 2015 Streaming, Distributed Variational Inference for Bayesian Nonparametrics NeurIPS 2015 Streaming Variational Inference for Bayesian Nonparametric Mixture Models AISTATS 2015 Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models NeurIPS 2015 Bayesian Logistic Gaussian Process Models for Dynamic Networks AISTATS 2014 Parallel Sampling of HDPs using Sub-Cluster Splits NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014 Bayesian Hierarchical Community Discovery NeurIPS 2013 Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture NeurIPS 2013 Memoized Online Variational Inference for Dirichlet Process Mixture Models NeurIPS 2013 Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation NeurIPS 2013 Real-Time Inference for a Gamma Process Model of Neural Spiking NeurIPS 2013 Bayesian Nonparametric Modeling of Suicide Attempts NeurIPS 2012 Bayesian nonparametric models for bipartite graphs NeurIPS 2012 Bayesian nonparametric models for ranked data NeurIPS 2012 Modelling Reciprocating Relationships with Hawkes Processes NeurIPS 2012 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Scalable imputation of genetic data with a discrete fragmentation-coagulation process NeurIPS 2012 Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models NeurIPS 2012