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"Provably Robust and Plausible Counterfactual Explanations for Neural ..."

Junqi Jiang et al. (2023)

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DOI: —

access: open

type: Conference or Workshop Paper

metadata version: 2024-05-13

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  - electronic edition @ mlr.press (open access)
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  dblp key:
  - conf/acml/JiangLL0T23
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  - https://dblp.org/rec/conf/acml/JiangLL0T23
Junqi Jiang, Jianglin Lan, Francesco Leofante, Antonio Rago, Francesca Toni:
Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation. ACML 2023: 582-597

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