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. 2105.07107
  4. Cited By
An Effective Baseline for Robustness to Distributional Shift

An Effective Baseline for Robustness to Distributional Shift

15 May 2021
S. Thulasidasan
Sushil Thapa
S. Dhaubhadel
Gopinath Chennupati
Tanmoy Bhattacharya
J. Bilmes
    OOD
    OODD
ArXivPDFHTML

Papers citing "An Effective Baseline for Robustness to Distributional Shift"

8 / 8 papers shown
Title
Robust Uncertainty Estimation for Classification of Maritime Objects
Robust Uncertainty Estimation for Classification of Maritime Objects
J. Becktor
Frederik E. T. Schöller
Evangelos Boukas
Lazaros Nalpantidis
UQCV
OOD
42
2
0
03 Jul 2023
Low-Entropy Latent Variables Hurt Out-of-Distribution Performance
Low-Entropy Latent Variables Hurt Out-of-Distribution Performance
Nandi Schoots
Dylan R. Cope
OODD
OOD
28
0
0
20 May 2023
Open-Set Semi-Supervised Object Detection
Open-Set Semi-Supervised Object Detection
Yen-Cheng Liu
Chih-Yao Ma
Xiaoliang Dai
Junjiao Tian
Peter Vajda
Zijian He
Z. Kira
19
22
0
29 Aug 2022
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD
  Training Data Estimate a Combination of the Same Core Quantities
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities
Julian Bitterwolf
Alexander Meinke
Maximilian Augustin
Matthias Hein
OODD
15
25
0
20 Jun 2022
Out of Distribution Detection on ImageNet-O
Out of Distribution Detection on ImageNet-O
Anugya Srivastava
S. Jain
Mugdha Thigle
OOD
57
5
0
23 Jan 2022
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
879
0
21 Oct 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
5,661
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
9,138
0
06 Jun 2015
1