Uncertainty Quantification

Modelling Uncertainty in Collaborative Document Quality Assessment EMNLP 2019 Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera CVPR 2019 Noise Contrastive Priors for Functional Uncertainty UAI 2019 On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks NeurIPS 2019 Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction CVPR 2019 Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters NeurIPS 2019 Quantifying Uncertainty in Online Regression Forests JMLR 2019 Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NeurIPS 2019 Striking the Right Balance With Uncertainty CVPR 2019 Towards Reliable Learning for High Stakes Applications AAAI 2019 Uncertainty on Asynchronous Time Event Prediction NeurIPS 2019 Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control NeurIPS 2019 Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty NeurIPS 2019 Verified Uncertainty Calibration NeurIPS 2019 What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions CVPR 2019 Accurate Uncertainties for Deep Learning Using Calibrated Regression ICML 2018 Discriminative Learning of Prediction Intervals AISTATS 2018 Evidential Deep Learning to Quantify Classification Uncertainty NeurIPS 2018 Implicit Probabilistic Integrators for ODEs NeurIPS 2018 Learning Confidence Sets using Support Vector Machines NeurIPS 2018 Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018 Learning under Misspecified Objective Spaces CoRL 2018 Predictive Uncertainty Estimation via Prior Networks NeurIPS 2018 Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty IJCAI 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning CoRL 2018