Uncertainty Quantification

Justification-Based Reliability in Machine Learning AAAI 2020 Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification JMLR 2020 Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles AAAI 2020 Model-Based Diagnosis with Uncertain Observations AAAI 2020 Multi-Hypothesis Machine Translation Evaluation ACL 2020 Non-Parametric Calibration for Classification AISTATS 2020 On the Inference Calibration of Neural Machine Translation ACL 2020 On the Uncertainty of Self-Supervised Monocular Depth Estimation CVPR 2020 Parametric Gaussian Process Regressors ICML 2020 Posterior Calibrated Training on Sentence Classification Tasks ACL 2020 Posterior sampling strategies based on discretized stochastic differential equations for machine learning applications JMLR 2020 Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models IJCAI 2020 Preventing Critical Scoring Errors in Short Answer Scoring with Confidence Estimation ACL 2020 Probabilistic Object Detection: Definition and Evaluation WACV 2020 Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract) AAAI 2020 Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes AAAI 2020 Temporal Logics Over Finite Traces with Uncertainty AAAI 2020 Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples NeurIPS 2020 Towards More Accurate Uncertainty Estimation In Text Classification EMNLP 2020 Training Binary Neural Networks using the Bayesian Learning Rule ICML 2020 Transferable Calibration with Lower Bias and Variance in Domain Adaptation NeurIPS 2020 Uncertain Natural Language Inference ACL 2020 Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents AAAI 2020 Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End CVPR 2020 Uncertainty-Aware Curriculum Learning for Neural Machine Translation ACL 2020