ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2106.03762
  4. Cited By
Frustratingly Easy Uncertainty Estimation for Distribution Shift

Frustratingly Easy Uncertainty Estimation for Distribution Shift

7 June 2021
Tiago Salvador
Vikram S. Voleti
Alexander Iannantuono
Adam M. Oberman
    OOD
    UQCV
ArXivPDFHTML

Papers citing "Frustratingly Easy Uncertainty Estimation for Distribution Shift"

4 / 4 papers shown
Title
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved
  Calibration and Model Selection in Unsupervised Domain Adaptation
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation
Taejong Joo
Diego Klabjan
48
1
0
16 Oct 2023
Improving model calibration with accuracy versus uncertainty
  optimization
Improving model calibration with accuracy versus uncertainty optimization
R. Krishnan
Omesh Tickoo
UQCV
190
157
0
14 Dec 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
278
5,695
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
289
9,167
0
06 Jun 2015
1