model calibration

Extracting Chemical-Protein Interactions via Calibrated Deep Neural Network and Self-training EMNLP 2020 Further Analysis of Outlier Detection with Deep Generative Models NeurIPS 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification NeurIPS 2020 Improving model calibration with accuracy versus uncertainty optimization NeurIPS 2020 PEP: Parameter Ensembling by Perturbation NeurIPS 2020 Recalibrating classifiers for interpretable abusive content detection EMNLP 2020 Regularizing Class-Wise Predictions via Self-Knowledge Distillation CVPR 2020 Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness NeurIPS 2020 Transferable Calibration with Lower Bias and Variance in Domain Adaptation NeurIPS 2020 A Simple Baseline for Bayesian Uncertainty in Deep Learning NeurIPS 2019 Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration NeurIPS 2019 Calibrating Deep Convolutional Gaussian Processes AISTATS 2019 Calibration tests in multi-class classification: A unifying framework NeurIPS 2019 Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift NeurIPS 2019 Evaluating model calibration in classification AISTATS 2019 Learning Optimized Risk Scores JMLR 2019 On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks NeurIPS 2019 When does label smoothing help? NeurIPS 2019 Analyzing Uncertainty in Neural Machine Translation ICML 2018 Joint Calibration of Ensemble of Exemplar SVMs CVPR 2015 Multivariate Regression with Calibration NeurIPS 2014