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Why You Should Not Trust Interpretations in Machine Learning:
  Adversarial Attacks on Partial Dependence Plots

Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots

29 April 2024
Xi Xin
Giles Hooker
Fei Huang
    AAML
ArXivPDFHTML

Papers citing "Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots"

3 / 3 papers shown
Title
Explainable AI the Latest Advancements and New Trends
Explainable AI the Latest Advancements and New Trends
Bowen Long
Enjie Liu
Renxi Qiu
Yanqing Duan
XAI
14
0
0
11 May 2025
Explainable AI needs formal notions of explanation correctness
Explainable AI needs formal notions of explanation correctness
Stefan Haufe
Rick Wilming
Benedict Clark
Rustam Zhumagambetov
Danny Panknin
Ahcène Boubekki
XAI
26
0
0
22 Sep 2024
Towards Explainability of Machine Learning Models in Insurance Pricing
Towards Explainability of Machine Learning Models in Insurance Pricing
Kevin Kuo
Danielle L. Lupton
21
13
0
24 Mar 2020
1