aleatoric uncertainty

Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning (Student Abstract) AAAI 2021 Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions NeurIPS 2021 Deep Evidential Regression NeurIPS 2020 Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NeurIPS 2020 Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles UAI 2020 Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty NeurIPS 2020 Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020 Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning MIDL 2020 Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels NeurIPS 2019 Face Alignment With Kernel Density Deep Neural Network ICCV 2019 Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians NeurIPS 2019 Single-Model Uncertainties for Deep Learning NeurIPS 2019 Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning ICML 2018 Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty IJCAI 2018 What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? NeurIPS 2017