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PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining
  CNNs

PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs

31 August 2021
V. Kamakshi
Uday Gupta
N. C. Krishnan
ArXivPDFHTML

Papers citing "PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs"

14 / 14 papers shown
Title
Concept Extraction for Time Series with ECLAD-ts
Concept Extraction for Time Series with ECLAD-ts
Antonia Holzapfel
Andres Felipe Posada-Moreno
Sebastian Trimpe
AI4TS
21
0
0
07 Apr 2025
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers
Éloi Zablocki
Valentin Gerard
Amaia Cardiel
Eric Gaussier
Matthieu Cord
Eduardo Valle
79
0
0
23 Nov 2024
Deep Model Interpretation with Limited Data : A Coreset-based Approach
Deep Model Interpretation with Limited Data : A Coreset-based Approach
Hamed Behzadi-Khormouji
José Oramas
SLR
23
0
0
01 Oct 2024
A survey on Concept-based Approaches For Model Improvement
A survey on Concept-based Approaches For Model Improvement
Avani Gupta
P. J. Narayanan
LRM
29
5
0
21 Mar 2024
SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc
  Explanation
SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation
Bo Pan
Zhenke Liu
Yifei Zhang
Liang Zhao
27
2
0
11 Oct 2023
Explainable AI for clinical risk prediction: a survey of concepts,
  methods, and modalities
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
Munib Mesinovic
Peter Watkinson
Ting Zhu
FaML
19
3
0
16 Aug 2023
Scalable Concept Extraction in Industry 4.0
Scalable Concept Extraction in Industry 4.0
Andres Felipe Posada-Moreno
K. Müller
Florian Brillowski
Friedrich Solowjow
T. Gries
Sebastian Trimpe
16
2
0
06 Jun 2023
FICNN: A Framework for the Interpretation of Deep Convolutional Neural
  Networks
FICNN: A Framework for the Interpretation of Deep Convolutional Neural Networks
Hamed Behzadi-Khormouji
José Oramas
11
0
0
17 May 2023
Multi-dimensional concept discovery (MCD): A unifying framework with
  completeness guarantees
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees
Johanna Vielhaben
Stefan Blücher
Nils Strodthoff
25
37
0
27 Jan 2023
Explainable Supervised Domain Adaptation
V. Kamakshi
N. C. Krishnan
30
2
0
20 May 2022
Sparse Subspace Clustering for Concept Discovery (SSCCD)
Sparse Subspace Clustering for Concept Discovery (SSCCD)
Johanna Vielhaben
Stefan Blücher
Nils Strodthoff
23
6
0
11 Mar 2022
Cause and Effect: Hierarchical Concept-based Explanation of Neural
  Networks
Cause and Effect: Hierarchical Concept-based Explanation of Neural Networks
Mohammad Nokhbeh Zaeem
Majid Komeili
CML
10
9
0
14 May 2021
Benchmarking and Survey of Explanation Methods for Black Box Models
Benchmarking and Survey of Explanation Methods for Black Box Models
F. Bodria
F. Giannotti
Riccardo Guidotti
Francesca Naretto
D. Pedreschi
S. Rinzivillo
XAI
33
219
0
25 Feb 2021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
Chih-Kuan Yeh
Been Kim
Sercan Ö. Arik
Chun-Liang Li
Tomas Pfister
Pradeep Ravikumar
FAtt
122
297
0
17 Oct 2019
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