Bayesian Inference

Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach JMLR 2022 Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network AAAI 2022 Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling JMLR 2022 Natural gradient enables fast sampling in spiking neural networks NeurIPS 2022 Natural image synthesis for the retina with variational information bottleneck representation NeurIPS 2022 Neural Contextual Bandits without Regret AISTATS 2022 Neural ensemble search via Bayesian sampling UAI 2022 Neural Point Process for Learning Spatiotemporal Event Dynamics L4DC 2022 NOMU: Neural Optimization-based Model Uncertainty ICML 2022 Non-Cheating Teaching Revisited: A New Probabilistic Machine Teaching Model IJCAI 2022 Nonlinear MCMC for Bayesian Machine Learning NeurIPS 2022 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022 Nonparametric Embeddings of Sparse High-Order Interaction Events ICML 2022 Nonparametric Involutive Markov Chain Monte Carlo ICML 2022 Nonparametric Relational Models with Superrectangulation AISTATS 2022 Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes ICML 2022 Nonparametric Uncertainty Quantification for Single Deterministic Neural Network NeurIPS 2022 Numerical Approximations of Log Gaussian Cox Process (Student Abstract) AAAI 2022 Obtaining Calibrated Probabilities with Personalized Ranking Models AAAI 2022 Offline Policy Selection under Uncertainty AISTATS 2022 On Divergence Measures for Bayesian Pseudocoresets NeurIPS 2022 Online Neural Sequence Detection with Hierarchical Dirichlet Point Process NeurIPS 2022 On Non-Random Missing Labels in Semi-Supervised Learning ICLR 2022 On provably robust meta-Bayesian optimization UAI 2022 On the benefits of maximum likelihood estimation for Regression and Forecasting ICLR 2022