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Do Input Gradients Highlight Discriminative Features?

Do Input Gradients Highlight Discriminative Features?

25 February 2021
Harshay Shah
Prateek Jain
Praneeth Netrapalli
    AAML
    FAtt
ArXivPDFHTML

Papers citing "Do Input Gradients Highlight Discriminative Features?"

14 / 14 papers shown
Title
Axiomatic Explainer Globalness via Optimal Transport
Axiomatic Explainer Globalness via Optimal Transport
Davin Hill
Josh Bone
A. Masoomi
Max Torop
Jennifer Dy
93
1
0
13 Mar 2025
Structured Gradient-based Interpretations via Norm-Regularized
  Adversarial Training
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training
Shizhan Gong
Qi Dou
Farzan Farnia
FAtt
35
2
0
06 Apr 2024
What Sketch Explainability Really Means for Downstream Tasks
What Sketch Explainability Really Means for Downstream Tasks
Hmrishav Bandyopadhyay
Pinaki Nath Chowdhury
A. Bhunia
Aneeshan Sain
Tao Xiang
Yi-Zhe Song
30
4
0
14 Mar 2024
3VL: Using Trees to Improve Vision-Language Models' Interpretability
3VL: Using Trees to Improve Vision-Language Models' Interpretability
Nir Yellinek
Leonid Karlinsky
Raja Giryes
CoGe
VLM
49
4
0
28 Dec 2023
Interpretability-Aware Vision Transformer
Interpretability-Aware Vision Transformer
Yao Qiang
Chengyin Li
Prashant Khanduri
D. Zhu
ViT
80
7
0
14 Sep 2023
Discriminative Feature Attributions: Bridging Post Hoc Explainability
  and Inherent Interpretability
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability
Usha Bhalla
Suraj Srinivas
Himabindu Lakkaraju
FAtt
CML
21
6
0
27 Jul 2023
Which Models have Perceptually-Aligned Gradients? An Explanation via
  Off-Manifold Robustness
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
Suraj Srinivas
Sebastian Bordt
Hima Lakkaraju
AAML
25
11
0
30 May 2023
Variational Information Pursuit for Interpretable Predictions
Variational Information Pursuit for Interpretable Predictions
Aditya Chattopadhyay
Kwan Ho Ryan Chan
B. Haeffele
D. Geman
René Vidal
DRL
15
10
0
06 Feb 2023
ModelDiff: A Framework for Comparing Learning Algorithms
ModelDiff: A Framework for Comparing Learning Algorithms
Harshay Shah
Sung Min Park
Andrew Ilyas
A. Madry
SyDa
46
26
0
22 Nov 2022
When are Post-hoc Conceptual Explanations Identifiable?
When are Post-hoc Conceptual Explanations Identifiable?
Tobias Leemann
Michael Kirchhof
Yao Rong
Enkelejda Kasneci
Gjergji Kasneci
50
10
0
28 Jun 2022
B-cos Networks: Alignment is All We Need for Interpretability
B-cos Networks: Alignment is All We Need for Interpretability
Moritz D Boehle
Mario Fritz
Bernt Schiele
26
84
0
20 May 2022
On Translation Invariance in CNNs: Convolutional Layers can Exploit
  Absolute Spatial Location
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
J. C. V. Gemert
209
232
0
16 Mar 2020
Adversarial examples from computational constraints
Adversarial examples from computational constraints
Sébastien Bubeck
Eric Price
Ilya P. Razenshteyn
AAML
62
230
0
25 May 2018
Trainability and Accuracy of Neural Networks: An Interacting Particle
  System Approach
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach
Grant M. Rotskoff
Eric Vanden-Eijnden
59
118
0
02 May 2018
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