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An Empirical Evaluation on Robustness and Uncertainty of Regularization
  Methods

An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods

9 March 2020
Sanghyuk Chun
Seong Joon Oh
Sangdoo Yun
Dongyoon Han
Junsuk Choe
Y. Yoo
    AAML
    OOD
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Papers citing "An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods"

12 / 12 papers shown
Title
Enhancing Multiple Reliability Measures via Nuisance-extended
  Information Bottleneck
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck
Jongheon Jeong
Sihyun Yu
Hankook Lee
Jinwoo Shin
AAML
44
0
0
24 Mar 2023
MixBoost: Improving the Robustness of Deep Neural Networks by Boosting
  Data Augmentation
MixBoost: Improving the Robustness of Deep Neural Networks by Boosting Data Augmentation
Zhendong Liu
Wenyu Jiang
Min Guo
Chongjun Wang
AAML
21
1
0
08 Dec 2022
On Pitfalls of Measuring Occlusion Robustness through Data Distortion
On Pitfalls of Measuring Occlusion Robustness through Data Distortion
Antonia Marcu
28
0
0
24 Nov 2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function
  Perspective
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective
Chanwoo Park
Sangdoo Yun
Sanghyuk Chun
AAML
21
32
0
21 Aug 2022
Exploring the Design of Adaptation Protocols for Improved Generalization
  and Machine Learning Safety
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety
Puja Trivedi
Danai Koutra
Jayaraman J. Thiagarajan
AAML
28
0
0
26 Jul 2022
Few-shot Font Generation with Weakly Supervised Localized
  Representations
Few-shot Font Generation with Weakly Supervised Localized Representations
Song Park
Sanghyuk Chun
Junbum Cha
Bado Lee
Hyunjung Shim
19
10
0
22 Dec 2021
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures
Dan Hendrycks
Andy Zou
Mantas Mazeika
Leonard Tang
Bo-wen Li
D. Song
Jacob Steinhardt
UQCV
23
137
0
09 Dec 2021
Observations on K-image Expansion of Image-Mixing Augmentation for
  Classification
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Joonhyun Jeong
Sungmin Cha
Jongwon Choi
Sangdoo Yun
Taesup Moon
Y. Yoo
VLM
21
6
0
08 Oct 2021
Evaluating Prediction-Time Batch Normalization for Robustness under
  Covariate Shift
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift
Zachary Nado
Shreyas Padhy
D. Sculley
Alexander DÁmour
Balaji Lakshminarayanan
Jasper Snoek
OOD
AI4TS
30
240
0
19 Jun 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
276
5,661
0
05 Dec 2016
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
291
3,110
0
04 Nov 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