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Uncertainty Quantification

746 papers

Papers per year

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2
68
163
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Papers

Uncertainty-Aware Bootstrap Learning for Joint Extraction on Distantly-Supervised Data ACL 2023
Efficient Out-of-Domain Detection for Sequence to Sequence Models ACL 2023
Ambiguity Meets Uncertainty: Investigating Uncertainty Estimation for Word Sense Disambiguation ACL 2023
When to Read Documents or QA History: On Unified and Selective Open-domain QA ACL 2023
Do Large Language Models Know What They Don’t Know? ACL 2023
Making Pre-trained Language Models both Task-solvers and Self-calibrators ACL 2023
Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023
Meta-Uncertainty in Bayesian Model Comparison AISTATS 2023
Kernel Conditional Moment Constraints for Confounding Robust Inference AISTATS 2023
Bayesian Optimization with Conformal Prediction Sets AISTATS 2023
Conformal Off-Policy Prediction AISTATS 2023
Faithful Heteroscedastic Regression with Neural Networks AISTATS 2023
Variational Boosted Soft Trees AISTATS 2023
Risk Bounds on Aleatoric Uncertainty Recovery AISTATS 2023
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023
On double-descent in uncertainty quantification in overparametrized models AISTATS 2023
Retrospective Uncertainties for Deep Models using Vine Copulas AISTATS 2023
Model-Based Uncertainty in Value Functions AISTATS 2023
Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023
On the Calibration of Probabilistic Classifier Sets AISTATS 2023
Improving Adaptive Conformal Prediction Using Self-Supervised Learning AISTATS 2023
Conformalized Unconditional Quantile Regression AISTATS 2023
A Blessing of Dimensionality in Membership Inference through Regularization AISTATS 2023
Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles AISTATS 2023
Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution CVPR 2023