Empirical Frequentist Coverage of Deep Learning Uncertainty
Quantification Procedures

Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures

6 October 2020

Papers citing "Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures"

12 / 12 papers shown

Title
On the Out-of-Distribution Coverage of Combining Split Conformal Prediction and Bayesian Deep Learning Paul Scemama Ariel Kapusta 40 0 0 21 Nov 2023
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 18 1 0 11 Aug 2023
Comparing the quality of neural network uncertainty estimates for classification problems Daniel Ries Joshua J. Michalenko T. Ganter R. Baiyasi Jason Adams UQCV BDL 29 1 0 11 Aug 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 15 0 0 31 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity Dennis Ulmer J. Frellsen Christian Hardmeier 189 22 0 20 Oct 2022
A review of predictive uncertainty estimation with machine learning Hristos Tyralis Georgia Papacharalampous UD UQCV 59 43 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 33 7 0 05 Aug 2022
Scalable computation of prediction intervals for neural networks via matrix sketching Alexander Fishkov Maxim Panov UQCV 30 1 0 06 May 2022
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 71 1,377 0 14 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer Giovanni Cina OODD 35 31 0 09 Dec 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015