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Using Pre-Training Can Improve Model Robustness and Uncertainty

Using Pre-Training Can Improve Model Robustness and Uncertainty

28 January 2019
Dan Hendrycks
Kimin Lee
Mantas Mazeika
    NoLa
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Papers citing "Using Pre-Training Can Improve Model Robustness and Uncertainty"

50 / 155 papers shown
Title
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
Adversarial Robustness through the Lens of Convolutional Filters
Adversarial Robustness through the Lens of Convolutional Filters
Paul Gavrikov
J. Keuper
38
15
0
05 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional
  Filters
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters
Paul Gavrikov
J. Keuper
AAML
24
31
0
29 Mar 2022
A Comparative Survey of Deep Active Learning
A Comparative Survey of Deep Active Learning
Xueying Zhan
Qingzhong Wang
Kuan-Hao Huang
Haoyi Xiong
Dejing Dou
Antoni B. Chan
FedML
HAI
24
105
0
25 Mar 2022
3D Common Corruptions and Data Augmentation
3D Common Corruptions and Data Augmentation
Oğuzhan Fatih Kar
Teresa Yeo
Andrei Atanov
Amir Zamir
3DPC
51
107
0
02 Mar 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Tianyu Pang
Min-Bin Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
30
119
0
21 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks
Robust Binary Models by Pruning Randomly-initialized Networks
Chen Liu
Ziqi Zhao
Sabine Süsstrunk
Mathieu Salzmann
TPM
AAML
MQ
29
4
0
03 Feb 2022
Investigating Transfer Learning in Graph Neural Networks
Investigating Transfer Learning in Graph Neural Networks
Nishai Kooverjee
Steven D. James
Terence L van Zyl
GNN
33
15
0
01 Feb 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing
  Adversarial Defenses
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
Mengting Xu
Tao Zhang
Zhongnian Li
Daoqiang Zhang
AAML
38
1
0
29 Jan 2022
Constrained Gradient Descent: A Powerful and Principled Evasion Attack
  Against Neural Networks
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
Weiran Lin
Keane Lucas
Lujo Bauer
Michael K. Reiter
Mahmood Sharif
AAML
31
5
0
28 Dec 2021
Ghost-dil-NetVLAD: A Lightweight Neural Network for Visual Place
  Recognition
Ghost-dil-NetVLAD: A Lightweight Neural Network for Visual Place Recognition
Qingyuan Gong
Yu Liu
Liqiang Zhang
Renhe Liu
ObjD
VLM
33
3
0
22 Dec 2021
Learning with Label Noise for Image Retrieval by Selecting Interactions
Learning with Label Noise for Image Retrieval by Selecting Interactions
Sarah Ibrahimi
Arnaud Sors
Rafael Sampaio de Rezende
S. Clinchant
NoLa
VLM
27
16
0
20 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in
  Adversarial Training
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
23
13
0
14 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
General Facial Representation Learning in a Visual-Linguistic Manner
General Facial Representation Learning in a Visual-Linguistic Manner
Yinglin Zheng
Hao Yang
Ting Zhang
Jianmin Bao
Dongdong Chen
Yangyu Huang
Lu Yuan
Dong Chen
Ming Zeng
Fang Wen
CVBM
146
163
0
06 Dec 2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial
  Robustness
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness
Konstantinos P. Panousis
S. Chatzis
Sergios Theodoridis
BDL
AAML
60
11
0
05 Dec 2021
Are Vision Transformers Robust to Patch Perturbations?
Are Vision Transformers Robust to Patch Perturbations?
Jindong Gu
Volker Tresp
Yao Qin
AAML
ViT
38
60
0
20 Nov 2021
Data Augmentation Can Improve Robustness
Data Augmentation Can Improve Robustness
Sylvestre-Alvise Rebuffi
Sven Gowal
D. A. Calian
Florian Stimberg
Olivia Wiles
Timothy A. Mann
AAML
17
270
0
09 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated
  Channel Maps
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Muhammad Awais
Fengwei Zhou
Chuanlong Xie
Jiawei Li
Sung-Ho Bae
Zhenguo Li
AAML
43
17
0
09 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based
  Adversarial Attacks
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Maksym Yatsura
J. H. Metzen
Matthias Hein
OOD
26
14
0
02 Nov 2021
Sample Selection for Fair and Robust Training
Sample Selection for Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
21
61
0
27 Oct 2021
AugMax: Adversarial Composition of Random Augmentations for Robust
  Training
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Haotao Wang
Chaowei Xiao
Jean Kossaifi
Zhiding Yu
Anima Anandkumar
Zhangyang Wang
27
106
0
26 Oct 2021
How and When Adversarial Robustness Transfers in Knowledge Distillation?
How and When Adversarial Robustness Transfers in Knowledge Distillation?
Rulin Shao
Ming Zhou
C. Bezemer
Cho-Jui Hsieh
AAML
27
17
0
22 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
188
879
0
21 Oct 2021
Robustness and Reliability When Training With Noisy Labels
Robustness and Reliability When Training With Noisy Labels
Amanda Olmin
Fredrik Lindsten
OOD
NoLa
24
14
0
07 Oct 2021
Pretraining & Reinforcement Learning: Sharpening the Axe Before Cutting
  the Tree
Pretraining & Reinforcement Learning: Sharpening the Axe Before Cutting the Tree
Saurav Kadavath
Samuel Paradis
Brian Yao
VLM
CLIP
OffRL
OnRL
20
1
0
06 Oct 2021
Post-hoc Models for Performance Estimation of Machine Learning Inference
Post-hoc Models for Performance Estimation of Machine Learning Inference
Xuechen Zhang
Samet Oymak
Jiasi Chen
UQCV
15
4
0
06 Oct 2021
Improving Neural Machine Translation by Bidirectional Training
Improving Neural Machine Translation by Bidirectional Training
Liang Ding
Di Wu
Dacheng Tao
29
29
0
16 Sep 2021
Adversarial Robustness for Unsupervised Domain Adaptation
Adversarial Robustness for Unsupervised Domain Adaptation
Muhammad Awais
Fengwei Zhou
Hang Xu
Lanqing Hong
Ping Luo
Sung-Ho Bae
Zhenguo Li
20
39
0
02 Sep 2021
Towards to Robust and Generalized Medical Image Segmentation Framework
Yurong Chen
OOD
33
3
0
09 Aug 2021
Triggering Failures: Out-Of-Distribution detection by learning from
  local adversarial attacks in Semantic Segmentation
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
Victor Besnier
Andrei Bursuc
David Picard
Alexandre Briot
UQCV
24
48
0
03 Aug 2021
FREE: Feature Refinement for Generalized Zero-Shot Learning
FREE: Feature Refinement for Generalized Zero-Shot Learning
Shiming Chen
Wenjie Wang
Beihao Xia
Qinmu Peng
Xinge You
Feng Zheng
Ling Shao
VLM
24
134
0
29 Jul 2021
The USYD-JD Speech Translation System for IWSLT 2021
The USYD-JD Speech Translation System for IWSLT 2021
Liang Ding
Di Wu
Dacheng Tao
29
16
0
24 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic
  Processors and Synthetic Gradients
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients
Alessandro Cappelli
Julien Launay
Laurent Meunier
Ruben Ohana
Iacopo Poli
AAML
24
4
0
06 Jul 2021
The Values Encoded in Machine Learning Research
The Values Encoded in Machine Learning Research
Abeba Birhane
Pratyusha Kalluri
Dallas Card
William Agnew
Ravit Dotan
Michelle Bao
38
274
0
29 Jun 2021
On the Robustness of Pretraining and Self-Supervision for a Deep
  Learning-based Analysis of Diabetic Retinopathy
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
Vignesh Srinivasan
Nils Strodthoff
Jackie Ma
Alexander Binder
Klaus-Robert Muller
Wojciech Samek
OOD
20
6
0
25 Jun 2021
Improving Uncertainty Calibration of Deep Neural Networks via Truth
  Discovery and Geometric Optimization
Improving Uncertainty Calibration of Deep Neural Networks via Truth Discovery and Geometric Optimization
Chunwei Ma
Ziyun Huang
Jiayi Xian
Mingchen Gao
Jinhui Xu
UQCV
33
14
0
25 Jun 2021
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction
  for Few-Shot Classification
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Lee
Sae-Young Chung
29
20
0
22 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations
Adversarial Training Helps Transfer Learning via Better Representations
Zhun Deng
Linjun Zhang
Kailas Vodrahalli
Kenji Kawaguchi
James Zou
GAN
36
52
0
18 Jun 2021
On Deep Neural Network Calibration by Regularization and its Impact on Refinement
Aditya Singh
Alessandro Bay
B. Sengupta
Andrea Mirabile
AAML
27
2
0
17 Jun 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion
  based Perception in Autonomous Driving Under Physical-World Attacks
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*
Ningfei Wang*
Chaowei Xiao
Dawei Yang
Jin Fang
Ruigang Yang
Qi Alfred Chen
Mingyan D. Liu
Bo-wen Li
AAML
24
217
0
17 Jun 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
Jie Jessie Ren
Stanislav Fort
J. Liu
Abhijit Guha Roy
Shreyas Padhy
Balaji Lakshminarayanan
UQCV
33
216
0
16 Jun 2021
Out-of-Scope Intent Detection with Self-Supervision and Discriminative
  Training
Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training
Li-Ming Zhan
Haowen Liang
Bo Liu
Lu Fan
Xiao-Ming Wu
Albert Y. S. Lam
OODD
18
75
0
16 Jun 2021
Learning Stable Classifiers by Transferring Unstable Features
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao
Shiyu Chang
Regina Barzilay
OOD
27
8
0
15 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization
Adversarial Robustness via Fisher-Rao Regularization
Marine Picot
Francisco Messina
Malik Boudiaf
Fabrice Labeau
Ismail Ben Ayed
Pablo Piantanida
AAML
28
23
0
12 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and Primer
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zhangyang Wang
J. Yadawa
21
31
0
09 Jun 2021
Improved OOD Generalization via Adversarial Training and Pre-training
Improved OOD Generalization via Adversarial Training and Pre-training
Mingyang Yi
Lu Hou
Jiacheng Sun
Lifeng Shang
Xin Jiang
Qun Liu
Zhi-Ming Ma
VLM
31
83
0
24 May 2021
Exploring Misclassifications of Robust Neural Networks to Enhance
  Adversarial Attacks
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks
Leo Schwinn
René Raab
A. Nguyen
Dario Zanca
Bjoern M. Eskofier
AAML
14
58
0
21 May 2021
When Human Pose Estimation Meets Robustness: Adversarial Algorithms and
  Benchmarks
When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarks
Jiahang Wang
Sheng Jin
Wentao Liu
Weizhong Liu
Chao Qian
Ping Luo
AAML
11
56
0
13 May 2021
Predicting Intraoperative Hypoxemia with Hybrid Inference Sequence
  Autoencoder Networks
Predicting Intraoperative Hypoxemia with Hybrid Inference Sequence Autoencoder Networks
Hanyang Liu
Michael C. Montana
Dingwen Li
Chase Renfroe
Thomas Kannampallil
Chenyang Lu
38
2
0
30 Apr 2021
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