uncertainty quantification

Amortized Bayesian Meta-Learning ICLR 2019 An asymptotic analysis of distributed nonparametric methods JMLR 2019 A Simple Baseline for Bayesian Uncertainty in Deep Learning NeurIPS 2019 Assumed Density Filtering Q-learning IJCAI 2019 BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning NeurIPS 2019 Bayesian Batch Active Learning as Sparse Subset Approximation NeurIPS 2019 Bayesian Hierarchical Dynamic Model for Human Action Recognition CVPR 2019 Bayesian Layers: A Module for Neural Network Uncertainty NeurIPS 2019 Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods ICLR 2019 Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning AAAI 2019 Bounding Box Regression With Uncertainty for Accurate Object Detection CVPR 2019 Bounding Uncertainty for Active Batch Selection AAAI 2019 Building Trust in Deep Learning System towards Automated Disease Detection AAAI 2019 Calibrating Deep Convolutional Gaussian Processes AISTATS 2019 Calibration tests in multi-class classification: A unifying framework NeurIPS 2019 Can You Trust This Prediction? Auditing Pointwise Reliability After Learning AISTATS 2019 Computing Full Conformal Prediction Set with Approximate Homotopy NeurIPS 2019 Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels NeurIPS 2019 Curious iLQR: Resolving Uncertainty in Model-based RL CoRL 2019 CXPlain: Causal Explanations for Model Interpretation under Uncertainty NeurIPS 2019 Debiased Bayesian inference for average treatment effects NeurIPS 2019 Deep Gamblers: Learning to Abstain with Portfolio Theory NeurIPS 2019 Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control IJCAI 2019 Differentially Private Bayesian Linear Regression NeurIPS 2019 Distribution calibration for regression ICML 2019