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Uncertainty Quantification

21 directly classified papers

Papers per year

Papers

General Uncertainty Estimation with Delta Variances AAAI 2025
Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification ACL 2024
Uncertainty-Aware GAN for Single Image Super Resolution AAAI 2024
Fixing Overconfidence in Dynamic Neural Networks WACV 2024
SURE: SUrvey REcipes for building reliable and robust deep networks CVPR 2024
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NIPS 2023
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis AAAI 2023
Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression ACL 2023
Confidence Calibration for Intent Detection via Hyperspherical Space and Rebalanced Accuracy-Uncertainty Loss AAAI 2022
Region-dependent temperature scaling for certainty calibration and application to class-imbalanced token classification ACL 2022
Deep Hybrid Models for Out-of-Distribution Detection CVPR 2022
Masksembles for Uncertainty Estimation CVPR 2021
Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks AAAI 2021
Multidimensional Uncertainty-Aware Evidential Neural Networks AAAI 2021
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression CVPR 2021
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network CVPR 2021
Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End CVPR 2020
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020
Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification AAAI 2020
Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences CVPR 2019
Incorporating Uncertainty into Deep Learning for Spoken Language Assessment ACL 2017