bayesian nonparametrics

Variational Inference for Sparse Gaussian Process Modulated Hawkes Process AAAI 2020 Accurate Uncertainty Estimation and Decomposition in Ensemble Learning NeurIPS 2019 Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior ICML 2019 Binary Space Partitioning Forest AISTATS 2019 Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach AISTATS 2019 Graph Convolutional Gaussian Processes ICML 2019 Inferring Task Goals and Constraints using Bayesian Nonparametric Inverse Reinforcement Learning CoRL 2019 Infinite Mixture Prototypes for Few-shot Learning ICML 2019 Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process NAACL 2019 Learning Models of Sequential Decision-Making with Partial Specification of Agent Behavior AAAI 2019 Nonparametric Bayesian Deep Networks with Local Competition ICML 2019 Random Clique Covers for Graphs with Local Density and Global Sparsity UAI 2019 Random Function Priors for Correlation Modeling ICML 2019 Statistical Model Aggregation via Parameter Matching NeurIPS 2019 The LORACs Prior for VAEs: Letting the Trees Speak for the Data AISTATS 2019 Variational Russian Roulette for Deep Bayesian Nonparametrics ICML 2019 A Bayesian Nonparametric View on Count-Min Sketch NeurIPS 2018 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018 Bayesian Nonparametric Spectral Estimation NeurIPS 2018 Clustering Induced Kernel Learning ACML 2018 Deep Bayesian Nonparametric Tracking ICML 2018 Dependent Relational Gamma Process Models for Longitudinal Networks ICML 2018 Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning IJCAI 2018 Metadata-dependent Infinite Poisson Factorization for Efficiently Modelling Sparse and Large Matrices in Recommendation IJCAI 2018 Nonparametric learning from Bayesian models with randomized objective functions NeurIPS 2018