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Discriminative Feature Attributions: Bridging Post Hoc Explainability
  and Inherent Interpretability

Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability

27 July 2023
Usha Bhalla
Suraj Srinivas
Himabindu Lakkaraju
    FAtt
    CML
ArXivPDFHTML

Papers citing "Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability"

6 / 6 papers shown
Title
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
Moritz Vandenhirtz
Julia E. Vogt
26
0
0
09 May 2025
Comprehensive Attribution: Inherently Explainable Vision Model with
  Feature Detector
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector
Xianren Zhang
Dongwon Lee
Suhang Wang
VLM
FAtt
40
3
0
27 Jul 2024
Inpainting the Gaps: A Novel Framework for Evaluating Explanation
  Methods in Vision Transformers
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers
Lokesh Badisa
Sumohana S. Channappayya
35
0
0
17 Jun 2024
An Unsupervised Approach to Achieve Supervised-Level Explainability in
  Healthcare Records
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records
Joakim Edin
Maria Maistro
Lars Maaløe
Lasse Borgholt
Jakob Drachmann Havtorn
Tuukka Ruotsalo
FAtt
27
2
0
13 Jun 2024
How Well Do Feature-Additive Explainers Explain Feature-Additive
  Predictors?
How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?
Zachariah Carmichael
Walter J. Scheirer
FAtt
25
4
0
27 Oct 2023
Have We Learned to Explain?: How Interpretability Methods Can Learn to
  Encode Predictions in their Interpretations
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
N. Jethani
Mukund Sudarshan
Yindalon Aphinyanagphongs
Rajesh Ranganath
FAtt
78
70
0
02 Mar 2021
1