Bayesian Inference

Local Differential Privacy for Bayesian Optimization AAAI 2021 Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models NeurIPS 2021 Locally Valid and Discriminative Prediction Intervals for Deep Learning Models NeurIPS 2021 Local policy search with Bayesian optimization NeurIPS 2021 Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Loss function based second-order Jensen inequality and its application to particle variational inference NeurIPS 2021 Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications NeurIPS 2021 Making Heads and Tails of Models with Marginal Calibration for Sparse Tagsets EMNLP 2021 Marginalised Gaussian Processes with Nested Sampling NeurIPS 2021 Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021 Masksembles for Uncertainty Estimation CVPR 2021 Maximal ancestral graph structure learning via exact search UAI 2021 Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021 Measure Transport with Kernel Stein Discrepancy AISTATS 2021 Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation ACL 2021 Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models NeurIPS 2021 Meta-Learning Divergences for Variational Inference AISTATS 2021 Meta-Learning Reliable Priors in the Function Space NeurIPS 2021 Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation ACL 2021 Meta-Thompson Sampling ICML 2021 Mirror Langevin Monte Carlo: the Case Under Isoperimetry NeurIPS 2021 Misspecification in Prediction Problems and Robustness via Improper Learning AISTATS 2021 Misspecified Gaussian Process Bandit Optimization NeurIPS 2021 Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021 Mixing Time of Metropolis-Hastings for Bayesian Community Detection JMLR 2021