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1907.07174
Cited By
Natural Adversarial Examples
16 July 2019
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
D. Song
OODD
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Papers citing
"Natural Adversarial Examples"
50 / 1,025 papers shown
Title
Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised
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Peter König
G. Pipa
Kai-Uwe Kühnberger
38
1
0
03 Feb 2021
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
Sangdoo Yun
Seong Joon Oh
Byeongho Heo
Dongyoon Han
Junsuk Choe
Sanghyuk Chun
414
142
0
13 Jan 2021
SyReNN: A Tool for Analyzing Deep Neural Networks
Matthew Sotoudeh
Aditya V. Thakur
AAML
GNN
32
16
0
09 Jan 2021
Why do classifier accuracies show linear trends under distribution shift?
Horia Mania
S. Sra
OOD
29
19
0
31 Dec 2020
Revisiting Edge Detection in Convolutional Neural Networks
Minh Le
Subhradeep Kayal
FAtt
15
13
0
25 Dec 2020
A Singular Value Perspective on Model Robustness
Malhar Jere
Maghav Kumar
F. Koushanfar
AAML
23
6
0
07 Dec 2020
Improved Handling of Motion Blur in Online Object Detection
Mohamed Sayed
Gabriel J. Brostow
AAML
27
23
0
29 Nov 2020
Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment
Jeonghoon Park
Kyungmin Jo
Daehoon Gwak
Jimin Hong
Jaegul Choo
Edward Choi
OODD
21
1
0
26 Nov 2020
Dissecting Image Crops
Basile Van Hoorick
Carl Vondrick
20
9
0
24 Nov 2020
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles
Christopher Clark
Mark Yatskar
Luke Zettlemoyer
26
61
0
07 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
77
670
0
06 Nov 2020
Defense-friendly Images in Adversarial Attacks: Dataset and Metrics for Perturbation Difficulty
Camilo Pestana
Wei Liu
D. Glance
Ajmal Mian
AAML
16
5
0
05 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks
Tao Bai
Jinqi Luo
Jun Zhao
AAML
49
8
0
03 Nov 2020
Why Do Better Loss Functions Lead to Less Transferable Features?
Simon Kornblith
Ting-Li Chen
Honglak Lee
Mohammad Norouzi
FaML
33
90
0
30 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
29
48
0
19 Oct 2020
Towards Resistant Audio Adversarial Examples
Tom Dörr
Karla Markert
Nicolas M. Muller
Konstantin Böttinger
AAML
22
7
0
14 Oct 2020
Deep Ensembles for Low-Data Transfer Learning
Basil Mustafa
C. Riquelme
J. Puigcerver
andAndré Susano Pinto
Daniel Keysers
N. Houlsby
FedML
OOD
27
22
0
14 Oct 2020
Representation learning from videos in-the-wild: An object-centric approach
Rob Romijnders
Aravindh Mahendran
Michael Tschannen
Josip Djolonga
Marvin Ritter
N. Houlsby
Mario Lucic
OCL
SSL
31
8
0
06 Oct 2020
FSD50K: An Open Dataset of Human-Labeled Sound Events
Eduardo Fonseca
Xavier Favory
Jordi Pons
F. Font
Xavier Serra
22
435
0
01 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff
Jacob R. Kauffmann
Robert A. Vandermeulen
G. Montavon
Wojciech Samek
Marius Kloft
Thomas G. Dietterich
Klaus-Robert Muller
UQCV
20
780
0
24 Sep 2020
Contextual Semantic Interpretability
Diego Marcos
Ruth C. Fong
Sylvain Lobry
Rémi Flamary
Nicolas Courty
D. Tuia
SSL
20
27
0
18 Sep 2020
MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li
Caiming Xiong
Guosheng Lin
26
94
0
17 Sep 2020
Defending Against Multiple and Unforeseen Adversarial Videos
Shao-Yuan Lo
Vishal M. Patel
AAML
31
23
0
11 Sep 2020
Measuring Massive Multitask Language Understanding
Dan Hendrycks
Collin Burns
Steven Basart
Andy Zou
Mantas Mazeika
D. Song
Jacob Steinhardt
ELM
RALM
34
3,891
0
07 Sep 2020
Estimating Example Difficulty Using Variance of Gradients
Chirag Agarwal
Daniel D'souza
Sara Hooker
210
107
0
26 Aug 2020
TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices
A. Wong
M. Famouri
Maya Pavlova
Siddharth Surana
67
33
0
10 Aug 2020
On Robustness and Transferability of Convolutional Neural Networks
Josip Djolonga
Jessica Yung
Michael Tschannen
Rob Romijnders
Lucas Beyer
...
D. Moldovan
Sylvain Gelly
N. Houlsby
Xiaohua Zhai
Mario Lucic
OOD
13
154
0
16 Jul 2020
Our Evaluation Metric Needs an Update to Encourage Generalization
Swaroop Mishra
Anjana Arunkumar
Chris Bryan
Chitta Baral
30
16
0
14 Jul 2020
Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation
Leonard E. van Dyck
W. Gruber
27
3
0
13 Jul 2020
A Critical Evaluation of Open-World Machine Learning
Liwei Song
Vikash Sehwag
A. Bhagoji
Prateek Mittal
AAML
24
8
0
08 Jul 2020
How benign is benign overfitting?
Amartya Sanyal
P. Dokania
Varun Kanade
Philip Torr
NoLa
AAML
23
57
0
08 Jul 2020
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks
Yunfei Liu
Xingjun Ma
James Bailey
Feng Lu
AAML
22
504
0
05 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori
Achal Dave
Vaishaal Shankar
Nicholas Carlini
Benjamin Recht
Ludwig Schmidt
OOD
22
533
0
01 Jul 2020
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider
E. Rusak
L. Eck
Oliver Bringmann
Wieland Brendel
Matthias Bethge
VLM
42
463
0
30 Jun 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks
Steven Basart
Norman Mu
Saurav Kadavath
Frank Wang
...
Samyak Parajuli
Mike Guo
D. Song
Jacob Steinhardt
Justin Gilmer
OOD
110
1,672
0
29 Jun 2020
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification
Alberto Olmo
Sailik Sengupta
S. Kambhampati
25
6
0
26 Jun 2020
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift
Zachary Nado
Shreyas Padhy
D. Sculley
Alexander DÁmour
Balaji Lakshminarayanan
Jasper Snoek
OOD
AI4TS
32
240
0
19 Jun 2020
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo
Sanghyuk Chun
Seong Joon Oh
Dongyoon Han
Sangdoo Yun
Gyuwan Kim
Youngjung Uh
Jung-Woo Ha
ODL
285
27
0
15 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks
Harshay Shah
Kaustav Tamuly
Aditi Raghunathan
Prateek Jain
Praneeth Netrapalli
AAML
18
348
0
13 Jun 2020
Mean-Field Approximation to Gaussian-Softmax Integral with Application to Uncertainty Estimation
Zhiyun Lu
Eugene Ie
Fei Sha
UQCV
BDL
17
14
0
13 Jun 2020
Calibrated neighborhood aware confidence measure for deep metric learning
Maryna Karpusha
Sunghee Yun
István Fehérvári
UQCV
FedML
19
2
0
08 Jun 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Andrew Ilyas
A. Madry
20
130
0
22 May 2020
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data
Alexander Robey
Hamed Hassani
George J. Pappas
OOD
43
42
0
20 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
152
371
0
09 May 2020
Reproduction of Lateral Inhibition-Inspired Convolutional Neural Network for Visual Attention and Saliency Detection
Filip Marcinek
11
0
0
05 May 2020
Improved Adversarial Training via Learned Optimizer
Yuanhao Xiong
Cho-Jui Hsieh
AAML
20
30
0
25 Apr 2020
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
55
1,985
0
16 Apr 2020
Pretrained Transformers Improve Out-of-Distribution Robustness
Dan Hendrycks
Xiaoyuan Liu
Eric Wallace
Adam Dziedzic
R. Krishnan
D. Song
OOD
10
429
0
13 Apr 2020
Editable Neural Networks
A. Sinitsin
Vsevolod Plokhotnyuk
Dmitriy V. Pyrkin
Sergei Popov
Artem Babenko
KELM
60
175
0
01 Apr 2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
Jan van Gemert
209
232
0
16 Mar 2020
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