Bayesian Inference

Accurate Uncertainty Estimation and Decomposition in Ensemble Learning NeurIPS 2019 A Contrastive Divergence for Combining Variational Inference and MCMC ICML 2019 Active Change-Point Detection ACML 2019 Active Multi-Information Source Bayesian Quadrature UAI 2019 Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces ICML 2019 Adaptive Gaussian Copula ABC AISTATS 2019 Adaptive MCMC via Combining Local Samplers AISTATS 2019 Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity AISTATS 2019 Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models AISTATS 2019 Adaptive Sensor Placement for Continuous Spaces ICML 2019 Adding Constraints to Bayesian Inverse Problems AAAI 2019 Addressing Failure Prediction by Learning Model Confidence NeurIPS 2019 ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM JMLR 2019 Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network ICLR 2019 Adversarial Imitation via Variational Inverse Reinforcement Learning ICLR 2019 Adversarial Variational Optimization of Non-Differentiable Simulators AISTATS 2019 A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles AAAI 2019 A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations UAI 2019 A Framework for Bayesian Optimization in Embedded Subspaces ICML 2019 AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling NeurIPS 2019 A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019 A Generalization Bound for Online Variational Inference ACML 2019 A Generative Adversarial Density Estimator CVPR 2019 Aligning Vector-spaces with Noisy Supervised Lexicon NAACL 2019 Alleviating Label Switching with Optimal Transport NeurIPS 2019