Uncertainty Quantification

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression CVPR 2021 Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network CVPR 2021 Masksembles for Uncertainty Estimation CVPR 2021 Multidimensional Uncertainty-Aware Evidential Neural Networks AAAI 2021 Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks AAAI 2021 Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020 Conservative Uncertainty Estimation By Fitting Prior Networks ICLR 2020 Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data CVPR 2020 Improving model calibration with accuracy versus uncertainty optimization NeurIPS 2020 LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood CVPR 2020 Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness NeurIPS 2020 Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End CVPR 2020 Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification AAAI 2020 Addressing Failure Prediction by Learning Model Confidence NeurIPS 2019 Bounding Box Regression With Uncertainty for Accurate Object Detection CVPR 2019 Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels NeurIPS 2019 Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences CVPR 2019 Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams ICLR 2019 Quantifying Uncertainties in Natural Language Processing Tasks AAAI 2019 Lightweight Probabilistic Deep Networks CVPR 2018 Structured Uncertainty Prediction Networks CVPR 2018 Incorporating Uncertainty into Deep Learning for Spoken Language Assessment ACL 2017 Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles NeurIPS 2017