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Sanity Checks for Saliency Maps

Sanity Checks for Saliency Maps

8 October 2018
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
    FAtt
    AAML
    XAI
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Papers citing "Sanity Checks for Saliency Maps"

50 / 357 papers shown
Title
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna
Tessa Han
Alex Gu
Steven Wu
S. Jabbari
Himabindu Lakkaraju
177
186
0
03 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning
Wencan Zhang
Mariella Dimiccoli
Brian Y. Lim
FAtt
19
1
0
30 Jan 2022
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
Alon Jacovi
Jasmijn Bastings
Sebastian Gehrmann
Yoav Goldberg
Katja Filippova
36
15
0
27 Jan 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial
  Contexts
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts
Sebastian Bordt
Michèle Finck
Eric Raidl
U. V. Luxburg
AILaw
39
77
0
25 Jan 2022
Deeply Explain CNN via Hierarchical Decomposition
Deeply Explain CNN via Hierarchical Decomposition
Mingg-Ming Cheng
Peng-Tao Jiang
Linghao Han
Liang Wang
Philip H. S. Torr
FAtt
53
15
0
23 Jan 2022
Topological Representations of Local Explanations
Topological Representations of Local Explanations
Peter Xenopoulos
G. Chan
Harish Doraiswamy
L. G. Nonato
Brian Barr
Claudio Silva
FAtt
22
4
0
06 Jan 2022
Global explainability in aligned image modalities
Global explainability in aligned image modalities
Justin Engelmann
Amos Storkey
Miguel O. Bernabeu
FAtt
30
4
0
17 Dec 2021
HIVE: Evaluating the Human Interpretability of Visual Explanations
HIVE: Evaluating the Human Interpretability of Visual Explanations
Sunnie S. Y. Kim
Nicole Meister
V. V. Ramaswamy
Ruth C. Fong
Olga Russakovsky
66
114
0
06 Dec 2021
Improving Deep Learning Interpretability by Saliency Guided Training
Improving Deep Learning Interpretability by Saliency Guided Training
Aya Abdelsalam Ismail
H. C. Bravo
S. Feizi
FAtt
20
80
0
29 Nov 2021
Evaluation of Interpretability for Deep Learning algorithms in EEG
  Emotion Recognition: A case study in Autism
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism
J. M. M. Torres
Sara E. Medina-DeVilliers
T. Clarkson
M. Lerner
Giuseppe Riccardi
30
34
0
25 Nov 2021
An Analysis of the Influence of Transfer Learning When Measuring the
  Tortuosity of Blood Vessels
An Analysis of the Influence of Transfer Learning When Measuring the Tortuosity of Blood Vessels
Matheus V. da Silva
Julie Ouellette
Baptiste Lacoste
C. H. Comin
24
7
0
19 Nov 2021
A Practical guide on Explainable AI Techniques applied on Biomedical use
  case applications
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications
Adrien Bennetot
Ivan Donadello
Ayoub El Qadi
M. Dragoni
Thomas Frossard
...
M. Trocan
Raja Chatila
Andreas Holzinger
Artur Garcez
Natalia Díaz Rodríguez
XAI
32
7
0
13 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation
Self-Interpretable Model with TransformationEquivariant Interpretation
Yipei Wang
Xiaoqian Wang
38
23
0
09 Nov 2021
Defense Against Explanation Manipulation
Defense Against Explanation Manipulation
Ruixiang Tang
Ninghao Liu
Fan Yang
Na Zou
Xia Hu
AAML
44
11
0
08 Nov 2021
Gradient Frequency Modulation for Visually Explaining Video
  Understanding Models
Gradient Frequency Modulation for Visually Explaining Video Understanding Models
Xinmiao Lin
Wentao Bao
Matthew Wright
Yu Kong
FAtt
AAML
22
2
0
01 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A
  Review of Interpretability Methods
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
Zohaib Salahuddin
Henry C. Woodruff
A. Chatterjee
Philippe Lambin
18
302
0
01 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual
  Explanations
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
Saumitra Mishra
Sanghamitra Dutta
Jason Long
Daniele Magazzeni
AAML
14
58
0
30 Oct 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift
  Detection
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
30
29
0
26 Oct 2021
VAC-CNN: A Visual Analytics System for Comparative Studies of Deep
  Convolutional Neural Networks
VAC-CNN: A Visual Analytics System for Comparative Studies of Deep Convolutional Neural Networks
Xiwei Xuan
Xiaoyu Zhang
Oh-Hyun Kwon
K. Ma
HAI
16
17
0
25 Oct 2021
Double Trouble: How to not explain a text classifier's decisions using
  counterfactuals synthesized by masked language models?
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models?
Thang M. Pham
Trung H. Bui
Long Mai
Anh Totti Nguyen
21
7
0
22 Oct 2021
TorchEsegeta: Framework for Interpretability and Explainability of
  Image-based Deep Learning Models
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models
S. Chatterjee
Arnab Das
Chirag Mandal
Budhaditya Mukhopadhyay
Manish Vipinraj
Aniruddh Shukla
R. Rao
Chompunuch Sarasaen
Oliver Speck
A. Nürnberger
MedIm
37
14
0
16 Oct 2021
Evaluating the Faithfulness of Importance Measures in NLP by Recursively
  Masking Allegedly Important Tokens and Retraining
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining
Andreas Madsen
Nicholas Meade
Vaibhav Adlakha
Siva Reddy
105
35
0
15 Oct 2021
The Irrationality of Neural Rationale Models
The Irrationality of Neural Rationale Models
Yiming Zheng
Serena Booth
J. Shah
Yilun Zhou
35
16
0
14 Oct 2021
TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency
TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency
Lin Cheng
Pengfei Fang
Yanjie Liang
Liao Zhang
Chunhua Shen
Hanzi Wang
FAtt
22
11
0
11 Oct 2021
Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess
Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess
Gregory Clark
25
9
0
05 Oct 2021
Consistent Explanations by Contrastive Learning
Consistent Explanations by Contrastive Learning
Vipin Pillai
Soroush Abbasi Koohpayegani
Ashley Ouligian
Dennis Fong
Hamed Pirsiavash
FAtt
20
21
0
01 Oct 2021
Focus! Rating XAI Methods and Finding Biases
Focus! Rating XAI Methods and Finding Biases
Anna Arias-Duart
Ferran Parés
Dario Garcia-Gasulla
Víctor Giménez-Ábalos
23
32
0
28 Sep 2021
Discriminative Attribution from Counterfactuals
Discriminative Attribution from Counterfactuals
N. Eckstein
A. S. Bates
G. Jefferis
Jan Funke
FAtt
CML
27
1
0
28 Sep 2021
Deep Learning-Based Detection of the Acute Respiratory Distress
  Syndrome: What Are the Models Learning?
Deep Learning-Based Detection of the Acute Respiratory Distress Syndrome: What Are the Models Learning?
Gregory B. Rehm
Chao Wang
I. Cortés-Puch
Chen-Nee Chuah
Jason Y. Adams
30
1
0
25 Sep 2021
From Heatmaps to Structural Explanations of Image Classifiers
From Heatmaps to Structural Explanations of Image Classifiers
Li Fuxin
Zhongang Qi
Saeed Khorram
Vivswan Shitole
Prasad Tadepalli
Minsuk Kahng
Alan Fern
XAI
FAtt
23
4
0
13 Sep 2021
IFBiD: Inference-Free Bias Detection
IFBiD: Inference-Free Bias Detection
Ignacio Serna
Daniel DeAlcala
Aythami Morales
Julian Fierrez
J. Ortega-Garcia
CVBM
39
11
0
09 Sep 2021
Deriving Explanation of Deep Visual Saliency Models
Deriving Explanation of Deep Visual Saliency Models
S. Malladi
J. Mukhopadhyay
M. Larabi
S. Chaudhury
FAtt
XAI
18
0
0
08 Sep 2021
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining
  CNNs
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs
V. Kamakshi
Uday Gupta
N. C. Krishnan
16
18
0
31 Aug 2021
Towards Out-Of-Distribution Generalization: A Survey
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CML
OOD
55
517
0
31 Aug 2021
Feature Importance in a Deep Learning Climate Emulator
Feature Importance in a Deep Learning Climate Emulator
Wei-ping Xu
Xihaier Luo
Yihui Ren
Ji Hwan Park
Shinjae Yoo
B. Nadiga
FAtt
AI4TS
33
3
0
27 Aug 2021
Longitudinal Distance: Towards Accountable Instance Attribution
Longitudinal Distance: Towards Accountable Instance Attribution
Rosina O. Weber
Prateek Goel
S. Amiri
G. Simpson
16
0
0
23 Aug 2021
Towards Interpretable Deep Networks for Monocular Depth Estimation
Towards Interpretable Deep Networks for Monocular Depth Estimation
Zunzhi You
Yi-Hsuan Tsai
W. Chiu
Guanbin Li
FAtt
31
17
0
11 Aug 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph
  Neural Networks
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks
Lucie Charlotte Magister
Dmitry Kazhdan
Vikash Singh
Pietro Lió
32
48
0
25 Jul 2021
Explainable artificial intelligence (XAI) in deep learning-based medical
  image analysis
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
Bas H. M. van der Velden
Hugo J. Kuijf
K. Gilhuijs
M. Viergever
XAI
29
636
0
22 Jul 2021
Robust Counterfactual Explanations on Graph Neural Networks
Robust Counterfactual Explanations on Graph Neural Networks
Mohit Bajaj
Lingyang Chu
Zihui Xue
J. Pei
Lanjun Wang
P. C. Lam
Yong Zhang
OOD
43
96
0
08 Jul 2021
Challenges for machine learning in clinical translation of big data
  imaging studies
Challenges for machine learning in clinical translation of big data imaging studies
Nicola K. Dinsdale
Emma Bluemke
V. Sundaresan
M. Jenkinson
Stephen Smith
Ana I. L. Namburete
AI4CE
32
41
0
07 Jul 2021
Knowledge-Grounded Self-Rationalization via Extractive and Natural
  Language Explanations
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations
Bodhisattwa Prasad Majumder
Oana-Maria Camburu
Thomas Lukasiewicz
Julian McAuley
25
35
0
25 Jun 2021
Evaluation of Saliency-based Explainability Method
Evaluation of Saliency-based Explainability Method
Sam Zabdiel Sunder Samuel
V. Kamakshi
Namrata Lodhi
N. C. Krishnan
FAtt
XAI
32
12
0
24 Jun 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine
  Learning
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning
Yang Liu
Sujay Khandagale
Colin White
W. Neiswanger
37
65
0
23 Jun 2021
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation
  Mapping for image saliency
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency
M. Jalwana
Naveed Akhtar
Bennamoun
Ajmal Saeed Mian
22
54
0
20 Jun 2021
Characterizing the risk of fairwashing
Characterizing the risk of fairwashing
Ulrich Aïvodji
Hiromi Arai
Sébastien Gambs
Satoshi Hara
23
27
0
14 Jun 2021
Certification of embedded systems based on Machine Learning: A survey
Certification of embedded systems based on Machine Learning: A survey
Guillaume Vidot
Christophe Gabreau
I. Ober
Iulian Ober
11
12
0
14 Jun 2021
Explaining Time Series Predictions with Dynamic Masks
Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé
M. Schaar
FAtt
AI4TS
23
80
0
09 Jun 2021
3DB: A Framework for Debugging Computer Vision Models
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
A. Madry
40
40
0
07 Jun 2021
A Holistic Approach to Interpretability in Financial Lending: Models,
  Visualizations, and Summary-Explanations
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations
Chaofan Chen
Kangcheng Lin
Cynthia Rudin
Yaron Shaposhnik
Sijia Wang
Tong Wang
19
41
0
04 Jun 2021
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