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2010.03039
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Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures
6 October 2020
Benjamin Kompa
Jasper Snoek
Andrew L. Beam
UQCV
BDL
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Papers citing
"Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures"
17 / 17 papers shown
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: Leveraging Geometry for Conformal Prediction via Canonicalization
Conference on Uncertainty in Artificial Intelligence (UAI), 2025
P. A. V. D. Linden
Alexander Timans
Erik J. Bekkers
231
1
0
19 Jun 2025
On the Out-of-Distribution Coverage of Combining Split Conformal Prediction and Bayesian Deep Learning
Paul Scemama
Ariel Kapusta
252
0
0
21 Nov 2023
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
Neural Information Processing Systems (NeurIPS), 2023
B. V. Breugel
Nabeel Seedat
F. Imrie
M. Schaar
SyDa
211
36
0
25 Oct 2023
Uncertainty Quantification for Image-based Traffic Prediction across Cities
Alexander Timans
Nina Wiedemann
Nishant Kumar
Ye Hong
Martin Raubal
200
1
0
11 Aug 2023
Comparing the quality of neural network uncertainty estimates for classification problems
International Conference on Machine Learning and Applications (ICMLA), 2022
Daniel Ries
Joshua J. Michalenko
T. Ganter
R. Baiyasi
Jason Adams
UQCV
BDL
182
1
0
11 Aug 2023
Uncertainty in Natural Language Generation: From Theory to Applications
Joris Baan
Nico Daheim
Evgenia Ilia
Dennis Ulmer
Haau-Sing Li
Raquel Fernández
Barbara Plank
Rico Sennrich
Chrysoula Zerva
Wilker Aziz
UQLM
468
63
0
28 Jul 2023
Conformal Prediction with Large Language Models for Multi-Choice Question Answering
Bhawesh Kumar
Cha-Chen Lu
Gauri Gupta
Anil Palepu
David R. Bellamy
Ramesh Raskar
Andrew L. Beam
430
101
0
28 May 2023
Confidence-Nets: A Step Towards better Prediction Intervals for regression Neural Networks on small datasets
M. Altayeb
A. Elamin
Hozaifa Ahmed
Eithar Elfatih Elfadil Ibrahim
Omer Haydar
Saba Abdulaziz
Najlaa H. M. Mohamed
UQCV
111
0
0
31 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Dennis Ulmer
J. Frellsen
Christian Hardmeier
433
27
0
20 Oct 2022
A review of predictive uncertainty estimation with machine learning
Artificial Intelligence Review (Artif Intell Rev), 2022
Hristos Tyralis
Georgia Papacharalampous
UD
UQCV
352
77
0
17 Sep 2022
Interpretable Uncertainty Quantification in AI for HEP
Thomas Y. Chen
B. Dey
A. Ghosh
Michael Kagan
Brian D. Nord
Nesar Ramachandra
205
13
0
05 Aug 2022
Scalable computation of prediction intervals for neural networks via matrix sketching
International Joint Conference on the Analysis of Images, Social Networks and Texts (AISNT), 2022
Alexander Fishkov
Maxim Panov
UQCV
124
1
0
06 May 2022
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation
Dennis Ulmer
Christian Hardmeier
J. Frellsen
BDL
UQCV
UD
EDL
PER
332
77
0
06 Oct 2021
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models
Neural Information Processing Systems (NeurIPS), 2021
Zhen Lin
Shubhendu Trivedi
Jimeng Sun
508
24
0
01 Jun 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
International Conference on Machine Learning (ICML), 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
670
1,646
0
14 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Dennis Ulmer
Giovanni Cina
OODD
595
34
0
09 Dec 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCV
BDL
799
517
0
17 Jun 2020
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