86 citations · 685 across the 45 of their papers we have counts for
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cs.CV2026
On the explainability of max-plus neural networks
Ikhlas Enaieh, Olivier Fercoq, García Ángel
We investigate the explanability properties of the recently proposed linear-min-max neural networks. At initialization, they can be interpreted as k-medoids with the infinity norm…
stat.ML2026
Exploiting Subgradient Sparsity in Max-Plus Neural Networks
Ikhlas Enaieh, Olivier Fercoq
Deep Neural Networks are powerful tools for solving machine learning problems, but their training often involves dense and costly parameter updates. In this work, we use a novel Ma…