Bayesian Inference

Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping MIDL 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020 Bayesian Meta Sampling for Fast Uncertainty Adaptation ICLR 2020 Bayesian Methods for Semi-supervised Text Annotation COLING 2020 Bayesian Model Selection with Graph Structured Sparsity JMLR 2020 Bayesian Network Model Averaging Classifiers by Subbagging PGM 2020 Bayesian network structure learning with causal effects in the presence of latent variables PGM 2020 Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract) AAAI 2020 Bayesian Optimisation over Multiple Continuous and Categorical Inputs ICML 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020 Bayesian Optimization for Iterative Learning NeurIPS 2020 Bayesian Optimization using Pseudo-Points IJCAI 2020 Bayesian Probabilistic Numerical Integration with Tree-Based Models NeurIPS 2020 Bayesian Pseudocoresets NeurIPS 2020 Bayesian Reinforcement Learning via Deep, Sparse Sampling AISTATS 2020 Bayesian Sparsification of Deep C-valued Networks ICML 2020 BayesOpt Adversarial Attack ICLR 2020 BayReL: Bayesian Relational Learning for Multi-omics Data Integration NeurIPS 2020 Being Bayesian about Categorical Probability ICML 2020 Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks ICML 2020 Bidirectional Convolutional Poisson Gamma Dynamical Systems NeurIPS 2020 BINOCULARS for efficient, nonmyopic sequential experimental design ICML 2020 Biomedical Entity Representations with Synonym Marginalization ACL 2020 Black-Box Inference for Non-Linear Latent Force Models AISTATS 2020 Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning ICLR 2020