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Enhanced Isotropy Maximization Loss: Seamless and High-Performance
  Out-of-Distribution Detection Simply Replacing the SoftMax Loss

Enhanced Isotropy Maximization Loss: Seamless and High-Performance Out-of-Distribution Detection Simply Replacing the SoftMax Loss

30 May 2021
David Macêdo
Teresa B Ludermir
    OODD
ArXivPDFHTML

Papers citing "Enhanced Isotropy Maximization Loss: Seamless and High-Performance Out-of-Distribution Detection Simply Replacing the SoftMax Loss"

7 / 7 papers shown
Title
Predictive Churn with the Set of Good Models
Predictive Churn with the Set of Good Models
J. Watson-Daniels
Flavio du Pin Calmon
Alexander DÁmour
Carol Xuan Long
David C. Parkes
Berk Ustun
83
7
0
12 Feb 2024
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label
  Non-conformity in Web Images Via a New Generalized KL Divergence
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label Non-conformity in Web Images Via a New Generalized KL Divergence
Xia Huang
Kai Fong Ernest Chong
42
2
0
19 Jul 2023
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution
  Detection and Uncertainty Estimation by Replacing the Loss and Calibrating
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution Detection and Uncertainty Estimation by Replacing the Loss and Calibrating
David Macêdo
Cleber Zanchettin
Teresa B Ludermir
UQCV
28
4
0
12 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via
  Distance-Awareness
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
J. Liu
Shreyas Padhy
Jie Jessie Ren
Zi Lin
Yeming Wen
Ghassen Jerfel
Zachary Nado
Jasper Snoek
Dustin Tran
Balaji Lakshminarayanan
UQCV
BDL
26
48
0
01 May 2022
Provably Robust Detection of Out-of-distribution Data (almost) for free
Provably Robust Detection of Out-of-distribution Data (almost) for free
Alexander Meinke
Julian Bitterwolf
Matthias Hein
OODD
33
22
0
08 Jun 2021
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
276
5,675
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
285
9,145
0
06 Jun 2015
1