Bayesian & Probabilistic

Matérn Gaussian Processes on Graphs AISTATS 2021 Matrix Product States for Inference in Discrete Probabilistic Models JMLR 2021 Maximal Couplings of the Metropolis-Hastings Algorithm AISTATS 2021 MCMC Variational Inference via Uncorrected Hamiltonian Annealing NeurIPS 2021 Measure Transport with Kernel Stein Discrepancy AISTATS 2021 Mercer Features for Efficient Combinatorial Bayesian Optimization AAAI 2021 Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models NeurIPS 2021 Meta-Learning Reliable Priors in the Function Space NeurIPS 2021 Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation ACL 2021 Min/max stability and box distributions UAI 2021 Misclassification Risk and Uncertainty Quantification in Deep Classifiers WACV 2021 Misspecified Gaussian Process Bandit Optimization NeurIPS 2021 Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling ICML 2021 Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021 Modeling the Probabilistic Distribution of Unlabeled Data for One-shot Medical Image Segmentation AAAI 2021 Model Selection for Bayesian Autoencoders NeurIPS 2021 Modular Gaussian Processes for Transfer Learning NeurIPS 2021 MOTS: Minimax Optimal Thompson Sampling ICML 2021 Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning ICLR 2021 Multidimensional Uncertainty-Aware Evidential Neural Networks AAAI 2021 Multi-output Gaussian Processes for uncertainty-aware recommender systems UAI 2021 Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference ICML 2021 Multi-view Inference for Relation Extraction with Uncertain Knowledge AAAI 2021 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021