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. 2207.07517
  4. Cited By
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution
  Detection

On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection

15 July 2022
Guoxuan Xia
C. Bouganis
    UQCV
ArXivPDFHTML

Papers citing "On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection"

14 / 14 papers shown
Title
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
Han Zhou
Jordy Van Landeghem
Teodora Popordanoska
Matthew B. Blaschko
111
3
0
20 Oct 2024
Deep Ensembles Work, But Are They Necessary?
Deep Ensembles Work, But Are They Necessary?
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
R. Zemel
John P. Cunningham
OOD
UQCV
111
63
0
14 Feb 2022
On the Out-of-distribution Generalization of Probabilistic Image
  Modelling
On the Out-of-distribution Generalization of Probabilistic Image Modelling
Mingtian Zhang
Andi Zhang
Jingyu Sun
OODD
53
45
0
04 Sep 2021
Understanding Softmax Confidence and Uncertainty
Understanding Softmax Confidence and Uncertainty
Tim Pearce
Alexandra Brintrup
Jun Zhu
UQCV
143
94
0
09 Jun 2021
Scaling Ensemble Distribution Distillation to Many Classes with Proxy
  Targets
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets
Max Ryabinin
A. Malinin
Mark Gales
UQCV
44
18
0
14 May 2021
What Are Bayesian Neural Network Posteriors Really Like?
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov
Sharad Vikram
Matthew D. Hoffman
A. Wilson
UQCV
BDL
69
385
0
29 Apr 2021
Energy-based Out-of-distribution Detection
Energy-based Out-of-distribution Detection
Weitang Liu
Xiaoyun Wang
John Douglas Owens
Yixuan Li
OODD
271
1,355
0
08 Oct 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning
  from Out-of-distribution Data
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
Yen-Chang Hsu
Yilin Shen
Hongxia Jin
Z. Kira
OODD
93
573
0
26 Feb 2020
Deep Ensembles: A Loss Landscape Perspective
Deep Ensembles: A Loss Landscape Perspective
Stanislav Fort
Huiyi Hu
Balaji Lakshminarayanan
OOD
UQCV
121
628
0
05 Dec 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PER
UD
231
1,411
0
21 Oct 2019
Natural Adversarial Examples
Natural Adversarial Examples
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
D. Song
OODD
200
1,469
0
16 Jul 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
164
1,691
0
06 Jun 2019
Do Deep Generative Models Know What They Don't Know?
Do Deep Generative Models Know What They Don't Know?
Eric T. Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Dilan Görür
Balaji Lakshminarayanan
OOD
63
757
0
22 Oct 2018
Describing Textures in the Wild
Describing Textures in the Wild
Mircea Cimpoi
Subhransu Maji
Iasonas Kokkinos
S. Mohamed
Andrea Vedaldi
3DV
119
2,671
0
14 Nov 2013
1