Uncertainty Quantification

Calibrating Structured Output Predictors for Natural Language Processing ACL 2020 Certifiably Adversarially Robust Detection of Out-of-Distribution Data NeurIPS 2020 Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics AAAI 2020 Computing Valid P-Values for Image Segmentation by Selective Inference CVPR 2020 Confidence-Aware Learning for Deep Neural Networks ICML 2020 Correcting Predictions for Approximate Bayesian Inference AAAI 2020 Data Uncertainty Learning in Face Recognition CVPR 2020 Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization AAAI 2020 Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification Interspeech 2020 Detecting Audio Attacks on ASR Systems with Dropout Uncertainty Interspeech 2020 Detecting Extrapolation with Local Ensembles ICLR 2020 Detecting Out-of-Distribution Examples with Gram Matrices ICML 2020 Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation ICML 2020 Efficient Predictive Uncertainty Estimators for Deep Probabilistic Models AAAI 2020 Ensemble Approaches for Uncertainty in Spoken Language Assessment Interspeech 2020 Estimating Model Uncertainty of Neural Networks in Sparse Information Form ICML 2020 Estimating predictive uncertainty for rumour verification models ACL 2020 Fairness Evaluation in Presence of Biased Noisy Labels AISTATS 2020 Flexible distribution-free conditional predictive bands using density estimators AISTATS 2020 GaSPing for Utility AAAI 2020 Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data CVPR 2020 Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks IJCAI 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification NeurIPS 2020 Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models NeurIPS 2020 Improving Confidence Estimates for Unfamiliar Examples CVPR 2020