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. 1901.06852
  4. Cited By
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at
  Label Shift Adaptation

Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation

21 January 2019
Amr M. Alexandari
A. Kundaje
Avanti Shrikumar
ArXivPDFHTML

Papers citing "Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation"

3 / 3 papers shown
Title
ReAct: Out-of-distribution Detection With Rectified Activations
ReAct: Out-of-distribution Detection With Rectified Activations
Yiyou Sun
Chuan Guo
Yixuan Li
OODD
43
457
0
24 Nov 2021
Analysis of the first Genetic Engineering Attribution Challenge
Analysis of the first Genetic Engineering Attribution Challenge
O. Crook
K. L. Warmbrod
G. Lipstein
Christine Chung
Christopher W. Bakerlee
...
Shelly R. Holland
Jacob Swett
K. Esvelt
E. C. Alley
W. Bradshaw
21
9
0
14 Oct 2021
Importance Weight Estimation and Generalization in Domain Adaptation
  under Label Shift
Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift
Kamyar Azizzadenesheli
OOD
29
13
0
29 Nov 2020
1