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Disproving XAI Myths with Formal Methods -- Initial Results

Disproving XAI Myths with Formal Methods -- Initial Results

13 May 2023
João Marques-Silva
ArXivPDFHTML

Papers citing "Disproving XAI Myths with Formal Methods -- Initial Results"

6 / 6 papers shown
Title
Logic-Based Explainability in Machine Learning
Logic-Based Explainability in Machine Learning
João Marques-Silva
LRM
XAI
31
39
0
24 Oct 2022
On Tackling Explanation Redundancy in Decision Trees
On Tackling Explanation Redundancy in Decision Trees
Yacine Izza
Alexey Ignatiev
João Marques-Silva
FAtt
48
56
0
20 May 2022
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
233
486
0
31 Dec 2020
Model Interpretability through the Lens of Computational Complexity
Model Interpretability through the Lens of Computational Complexity
Pablo Barceló
Mikaël Monet
Jorge A. Pérez
Bernardo Subercaseaux
114
93
0
23 Oct 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
294
4,187
0
23 Aug 2019
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,233
0
24 Jun 2017
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