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Interpreting Interpretations: Organizing Attribution Methods by Criteria

Interpreting Interpretations: Organizing Attribution Methods by Criteria

19 February 2020
Zifan Wang
Piotr (Peter) Mardziel
Anupam Datta
Matt Fredrikson
    XAI
    FAtt
ArXivPDFHTML

Papers citing "Interpreting Interpretations: Organizing Attribution Methods by Criteria"

7 / 7 papers shown
Title
Mapping Knowledge Representations to Concepts: A Review and New
  Perspectives
Mapping Knowledge Representations to Concepts: A Review and New Perspectives
Lars Holmberg
P. Davidsson
Per Linde
34
1
0
31 Dec 2022
What Makes a Good Explanation?: A Harmonized View of Properties of
  Explanations
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations
Zixi Chen
Varshini Subhash
Marton Havasi
Weiwei Pan
Finale Doshi-Velez
XAI
FAtt
33
18
0
10 Nov 2022
Faithful Explanations for Deep Graph Models
Faithful Explanations for Deep Graph Models
Zifan Wang
Yuhang Yao
Chaoran Zhang
Han Zhang
Youjie Kang
Carlee Joe-Wong
Matt Fredrikson
Anupam Datta
FAtt
19
2
0
24 May 2022
Robust Models Are More Interpretable Because Attributions Look Normal
Robust Models Are More Interpretable Because Attributions Look Normal
Zifan Wang
Matt Fredrikson
Anupam Datta
OOD
FAtt
30
25
0
20 Mar 2021
Evaluating and Aggregating Feature-based Model Explanations
Evaluating and Aggregating Feature-based Model Explanations
Umang Bhatt
Adrian Weller
J. M. F. Moura
XAI
30
218
0
01 May 2020
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
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