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Using Causal Analysis for Conceptual Deep Learning Explanation

Using Causal Analysis for Conceptual Deep Learning Explanation

10 July 2021
Sumedha Singla
Stephen Wallace
Sofia Triantafillou
Kayhan Batmanghelich
    CML
ArXiv (abs)PDFHTML

Papers citing "Using Causal Analysis for Conceptual Deep Learning Explanation"

12 / 12 papers shown
Title
Understanding the Role of Individual Units in a Deep Neural Network
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
72
453
0
10 Sep 2020
Deep Learning for Screening COVID-19 using Chest X-Ray Images
Deep Learning for Screening COVID-19 using Chest X-Ray Images
S. Basu
Sushmita Mitra
N. Saha
53
180
0
22 Apr 2020
Explanation by Progressive Exaggeration
Explanation by Progressive Exaggeration
Sumedha Singla
Brian Pollack
Junxiang Chen
Kayhan Batmanghelich
FAttMedIm
96
103
0
01 Nov 2019
Global and Local Interpretability for Cardiac MRI Classification
Global and Local Interpretability for Cardiac MRI Classification
J. Clough
Ilkay Oksuz
Esther Puyol-Antón
B. Ruijsink
A. King
Julia A. Schnabel
79
61
0
14 Jun 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and
  Expert Comparison
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Jeremy Irvin
Pranav Rajpurkar
M. Ko
Yifan Yu
Silviana Ciurea-Ilcus
...
D. Larson
C. Langlotz
Bhavik Patel
M. Lungren
A. Ng
118
2,604
0
21 Jan 2019
Interpretability Beyond Feature Attribution: Quantitative Testing with
  Concept Activation Vectors (TCAV)
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim
Martin Wattenberg
Justin Gilmer
Carrie J. Cai
James Wexler
F. Viégas
Rory Sayres
FAtt
248
1,849
0
30 Nov 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,090
0
22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual
  Representations
Network Dissection: Quantifying Interpretability of Deep Visual Representations
David Bau
Bolei Zhou
A. Khosla
A. Oliva
Antonio Torralba
MILMFAtt
158
1,526
1
19 Apr 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
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
335
20,110
0
07 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
828
36,892
0
25 Aug 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
Direct and Indirect Effects
Direct and Indirect Effects
Judea Pearl
CML
100
2,179
0
10 Jan 2013
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