confidence calibration

MSNet: A Multilevel Instance Segmentation Network for Natural Disaster Damage Assessment in Aerial Videos WACV 2021 Self-Knowledge Distillation With Progressive Refinement of Targets ICCV 2021 SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness NeurIPS 2021 When in Doubt: Improving Classification Performance with Alternating Normalization EMNLP 2021 Binary Classification from Positive Data with Skewed Confidence IJCAI 2020 Calibrating Structured Output Predictors for Natural Language Processing ACL 2020 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks ICML 2020 Detecting Out-of-Distribution Examples with Gram Matrices ICML 2020 Distance-Based Learning from Errors for Confidence Calibration ICLR 2020 Improving Confidence Estimates for Unfamiliar Examples CVPR 2020 Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks NeurIPS 2020 On the Inference Calibration of Neural Machine Translation ACL 2020 Selective Question Answering under Domain Shift ACL 2020 Adaptive Confidence Smoothing for Generalized Zero-Shot Learning CVPR 2019 Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences CVPR 2019 Towards Reliable Learning for High Stakes Applications AAAI 2019 Using Pre-Training Can Improve Model Robustness and Uncertainty ICML 2019 Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem CVPR 2019 Hierarchical Novelty Detection for Visual Object Recognition CVPR 2018 Pathologies of Neural Models Make Interpretations Difficult EMNLP 2018 Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings ICML 2018 Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples ICLR 2018 On Calibration of Modern Neural Networks ICML 2017 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 Calibrated Structured Prediction NeurIPS 2015