calibration error

Better Uncertainty Calibration via Proper Scores for Classification and Beyond NeurIPS 2022 Calibration Error for Heterogeneous Treatment Effects AISTATS 2022 Faster online calibration without randomization: interval forecasts and the power of two choices COLT 2022 Introspective Learning : A Two-Stage approach for Inference in Neural Networks NeurIPS 2022 Logit Mixing Training for More Reliable and Accurate Prediction IJCAI 2022 Mitigating Bias in Calibration Error Estimation AISTATS 2022 Platt-Bin: Efficient Posterior Calibrated Training for NLP Classifiers ACL 2022 Region-dependent temperature scaling for certainty calibration and application to class-imbalanced token classification ACL 2022 Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis EMNLP 2022 Understanding Square Loss in Training Overparametrized Neural Network Classifiers NeurIPS 2022 Active Bayesian Assessment of Black-Box Classifiers AAAI 2021 Deep Neural Network Calibration for E2E Speech Recognition System Interspeech 2021 Making Heads and Tails of Models with Marginal Calibration for Sparse Tagsets EMNLP 2021 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking ICML 2021 Training independent subnetworks for robust prediction ICLR 2021 Uncertainty Quantification and Deep Ensembles NeurIPS 2021 Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020 Calibrated Reliable Regression using Maximum Mean Discrepancy NeurIPS 2020 Calibration of Pre-trained Transformers EMNLP 2020 Improving Confidence Estimates for Unfamiliar Examples CVPR 2020 Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning CoRL 2020 Posterior Calibrated Training on Sentence Classification Tasks ACL 2020 Sample Complexity of Uniform Convergence for Multicalibration NeurIPS 2020 A Calibration Metric for Risk Scores with Survival Data MLHC 2019 Verified Uncertainty Calibration NeurIPS 2019