Nonparametric Bayesian

Variational Inference for Sparse Gaussian Process Modulated Hawkes Process AAAI 2020 Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data AAAI 2019 Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees NeurIPS 2019 Scalable inference of topic evolution via models for latent geometric structures NeurIPS 2019 A Bayesian Nonparametric View on Count-Min Sketch NeurIPS 2018 Clustering Induced Kernel Learning ACML 2018 Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks NeurIPS 2018 Rectangular Bounding Process NeurIPS 2018 Bayesian Dyadic Trees and Histograms for Regression NeurIPS 2017 Convergence rates of a partition based Bayesian multivariate density estimation method NeurIPS 2017 Noise-Clustered Distant Supervision for Relation Extraction: A Nonparametric Bayesian Perspective EMNLP 2017 YASS: Yet Another Spike Sorter NeurIPS 2017 A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics NeurIPS 2016 A Probabilistic Programming Approach To Probabilistic Data Analysis NeurIPS 2016 Completely random measures for modelling block-structured sparse networks NeurIPS 2016 Edge-exchangeable graphs and sparsity NeurIPS 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NeurIPS 2016 Flexible Models for Microclustering with Application to Entity Resolution NeurIPS 2016 Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NeurIPS 2016 Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics NeurIPS 2016 Poisson-Gamma dynamical systems NeurIPS 2016 Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models NeurIPS 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 Infinite Factorial Dynamical Model NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models NeurIPS 2015