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2110.04301
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Salient ImageNet: How to discover spurious features in Deep Learning?
8 October 2021
Sahil Singla
Soheil Feizi
AAML
VLM
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Papers citing
"Salient ImageNet: How to discover spurious features in Deep Learning?"
43 / 43 papers shown
Title
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
Simone Bombari
Marco Mondelli
177
0
0
03 Feb 2025
Sebra: Debiasing Through Self-Guided Bias Ranking
Adarsh Kappiyath
Abhra Chaudhuri
Ajay Jaiswal
Ziquan Liu
Yunpeng Li
Xiatian Zhu
L. Yin
CML
347
1
1
30 Jan 2025
3DB: A Framework for Debugging Computer Vision Models
Guillaume Leclerc
Hadi Salman
Andrew Ilyas
Sai H. Vemprala
Logan Engstrom
...
Pengchuan Zhang
Shibani Santurkar
Greg Yang
Ashish Kapoor
Aleksander Madry
57
40
0
07 Jun 2021
Finding and Fixing Spurious Patterns with Explanations
Gregory Plumb
Marco Tulio Ribeiro
Ameet Talwalkar
60
41
0
03 Jun 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong
Shibani Santurkar
Aleksander Madry
FAtt
44
90
0
11 May 2021
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Fereshte Khani
Percy Liang
FaML
39
65
0
07 Dec 2020
Understanding Failures of Deep Networks via Robust Feature Extraction
Sahil Singla
Besmira Nushi
S. Shah
Ece Kamar
Eric Horvitz
FAtt
45
83
0
03 Dec 2020
Benchmarking Deep Learning Interpretability in Time Series Predictions
Aya Abdelsalam Ismail
Mohamed K. Gunady
H. C. Bravo
Soheil Feizi
XAI
AI4TS
FAtt
31
169
0
26 Oct 2020
Understanding the Role of Individual Units in a Deep Neural Network
David Bau
Jun-Yan Zhu
Hendrik Strobelt
Àgata Lapedriza
Bolei Zhou
Antonio Torralba
GAN
52
446
0
10 Sep 2020
Generative causal explanations of black-box classifiers
Matthew R. O’Shaughnessy
Gregory H. Canal
Marissa Connor
Mark A. Davenport
Christopher Rozell
CML
45
73
0
24 Jun 2020
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Y. Xiao
Logan Engstrom
Andrew Ilyas
Aleksander Madry
119
384
0
17 Jun 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Andrew Ilyas
Aleksander Madry
53
132
0
22 May 2020
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Marco Tulio Ribeiro
Tongshuang Wu
Carlos Guestrin
Sameer Singh
ELM
145
1,089
0
08 May 2020
Debiasing Skin Lesion Datasets and Models? Not So Fast
Alceu Bissoto
Eduardo Valle
Sandra Avila
78
55
0
23 Apr 2020
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks
Aya Abdelsalam Ismail
Mohamed K. Gunady
L. Pessoa
H. C. Bravo
Soheil Feizi
AI4TS
59
50
0
27 Oct 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan
Quoc V. Le
3DV
MedIm
123
17,950
0
28 May 2019
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
Sahil Singla
Eric Wallace
Shi Feng
Soheil Feizi
FAtt
50
59
0
01 Feb 2019
On the (In)fidelity and Sensitivity for Explanations
Chih-Kuan Yeh
Cheng-Yu Hsieh
A. Suggala
David I. Inouye
Pradeep Ravikumar
FAtt
58
449
0
27 Jan 2019
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAtt
AAML
XAI
118
1,947
0
08 Oct 2018
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure
Besmira Nushi
Ece Kamar
Eric Horvitz
32
140
0
19 Sep 2018
Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models
Jiawei Zhang
Yang Wang
Piero Molino
Lezhi Li
D. Ebert
FAtt
46
203
0
01 Aug 2018
Explaining Image Classifiers by Counterfactual Generation
C. Chang
Elliot Creager
Anna Goldenberg
David Duvenaud
VLM
51
265
0
20 Jul 2018
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach
Yeounoh Chung
Tim Kraska
N. Polyzotis
Ki Hyun Tae
Steven Euijong Whang
61
131
0
16 Jul 2018
Recognition in Terra Incognita
Sara Beery
Grant Van Horn
Pietro Perona
78
835
0
13 Jul 2018
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
88
1,772
0
30 May 2018
Interpreting Deep Visual Representations via Network Dissection
Bolei Zhou
David Bau
A. Oliva
Antonio Torralba
FAtt
MILM
53
324
0
15 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
238
11,962
0
19 Jun 2017
SmoothGrad: removing noise by adding noise
D. Smilkov
Nikhil Thorat
Been Kim
F. Viégas
Martin Wattenberg
FAtt
ODL
192
2,215
0
12 Jun 2017
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
142
2,854
0
14 Mar 2017
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
142
5,920
0
04 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
225
19,796
0
07 Oct 2016
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
277
7,951
0
23 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
681
16,828
0
16 Feb 2016
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks
Anh Totti Nguyen
J. Yosinski
Jeff Clune
49
327
0
11 Feb 2016
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSL
SSeg
FAtt
186
9,280
0
14 Dec 2015
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.5K
192,638
0
10 Dec 2015
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images
Aravindh Mahendran
Andrea Vedaldi
FAtt
61
532
0
07 Dec 2015
Understanding Neural Networks Through Deep Visualization
J. Yosinski
Jeff Clune
Anh Totti Nguyen
Thomas J. Fuchs
Hod Lipson
FAtt
AI4CE
104
1,866
0
22 Jun 2015
Inverting Visual Representations with Convolutional Networks
Alexey Dosovitskiy
Thomas Brox
SSL
FAtt
61
662
0
09 Jun 2015
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
136
3,261
0
05 Dec 2014
Understanding Deep Image Representations by Inverting Them
Aravindh Mahendran
Andrea Vedaldi
FAtt
94
1,959
0
26 Nov 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
207
7,252
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
376
15,825
0
12 Nov 2013
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