Uncertainty Quantification

The Uncertainty Bellman Equation and Exploration ICML 2018 To Trust Or Not To Trust A Classifier NeurIPS 2018 Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings ICML 2018 Concrete Dropout NeurIPS 2017 Incorporating Uncertainty into Deep Learning for Spoken Language Assessment ACL 2017 Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models RSS 2017 Selective Classification for Deep Neural Networks NeurIPS 2017 Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CoRL 2017 Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models JMLR 2016 Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests JMLR 2016 Large-scale probabilistic predictors with and without guarantees of validity NeurIPS 2015 Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes NeurIPS 2015 Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation CVPR 2014 A Stepwise uncertainty reduction approach to constrained global optimization AISTATS 2014 Efficiency of conformalized ridge regression COLT 2014 Predicting Failures of Vision Systems CVPR 2014 Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics AISTATS 2014 Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification ICML 2014 Scaling Up Robust MDPs using Function Approximation ICML 2014 Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NeurIPS 2014 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models NeurIPS 2013 It's Not Polite to Point: Describing People with Uncertain Attributes CVPR 2013 Synthesizing Robust Plans under Incomplete Domain Models NeurIPS 2013 What do row and column marginals reveal about your dataset? NeurIPS 2013 Minimizing Uncertainty in Pipelines NeurIPS 2012