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What does LIME really see in images?

What does LIME really see in images?

11 February 2021
Damien Garreau
Dina Mardaoui
    FAtt
ArXivPDFHTML

Papers citing "What does LIME really see in images?"

17 / 17 papers shown
Title
Study on the Helpfulness of Explainable Artificial Intelligence
Study on the Helpfulness of Explainable Artificial Intelligence
Tobias Labarta
Elizaveta Kulicheva
Ronja Froelian
Christian Geißler
Xenia Melman
Julian von Klitzing
ELM
33
0
0
14 Oct 2024
Provably Better Explanations with Optimized Aggregation of Feature
  Attributions
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker
Ananta R. Bhattarai
Jindong Gu
Volker Tresp
Florian Buettner
28
2
0
07 Jun 2024
CAM-Based Methods Can See through Walls
CAM-Based Methods Can See through Walls
Magamed Taimeskhanov
R. Sicre
Damien Garreau
21
1
0
02 Apr 2024
Using Stratified Sampling to Improve LIME Image Explanations
Using Stratified Sampling to Improve LIME Image Explanations
Muhammad Rashid
E. Amparore
Enrico Ferrari
Damiano Verda
FAtt
17
2
0
26 Mar 2024
SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the
  Survival Models
SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models
Lev V. Utkin
Danila Eremenko
A. Konstantinov
23
0
0
11 Dec 2023
GLIME: General, Stable and Local LIME Explanation
GLIME: General, Stable and Local LIME Explanation
Zeren Tan
Yang Tian
Jian Li
FAtt
LRM
13
19
0
27 Nov 2023
Fairness Explainability using Optimal Transport with Applications in
  Image Classification
Fairness Explainability using Optimal Transport with Applications in Image Classification
Philipp Ratz
Franccois Hu
Arthur Charpentier
20
0
0
22 Aug 2023
On the Robustness of Text Vectorizers
On the Robustness of Text Vectorizers
R. Catellier
Samuel Vaiter
Damien Garreau
OOD
26
2
0
09 Mar 2023
Stop overkilling simple tasks with black-box models and use transparent models instead
Matteo Rizzo
Matteo Marcuzzo
A. Zangari
A. Gasparetto
A. Albarelli
VLM
21
0
0
06 Feb 2023
Identifying Spurious Correlations and Correcting them with an
  Explanation-based Learning
Identifying Spurious Correlations and Correcting them with an Explanation-based Learning
Misgina Tsighe Hagos
Kathleen M. Curran
Brian Mac Namee
20
10
0
15 Nov 2022
A Survey of Computer Vision Technologies In Urban and
  Controlled-environment Agriculture
A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture
Jiayun Luo
Boyang Albert Li
Cyril Leung
53
11
0
20 Oct 2022
The Manifold Hypothesis for Gradient-Based Explanations
The Manifold Hypothesis for Gradient-Based Explanations
Sebastian Bordt
Uddeshya Upadhyay
Zeynep Akata
U. V. Luxburg
FAtt
AAML
28
12
0
15 Jun 2022
How to scale hyperparameters for quickshift image segmentation
How to scale hyperparameters for quickshift image segmentation
Damien Garreau
13
1
0
23 Jan 2022
An Imprecise SHAP as a Tool for Explaining the Class Probability
  Distributions under Limited Training Data
An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data
Lev V. Utkin
A. Konstantinov
Kirill Vishniakov
FAtt
29
5
0
16 Jun 2021
Ensembles of Random SHAPs
Ensembles of Random SHAPs
Lev V. Utkin
A. Konstantinov
FAtt
16
20
0
04 Mar 2021
An Analysis of LIME for Text Data
An Analysis of LIME for Text Data
Dina Mardaoui
Damien Garreau
FAtt
134
45
0
23 Oct 2020
Looking Deeper into Tabular LIME
Looking Deeper into Tabular LIME
Damien Garreau
U. V. Luxburg
FAtt
LMTD
104
30
0
25 Aug 2020
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