4 citations · 5 across the 5 of their papers we have counts for
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cs.LG2020
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks
Reda Marzouk
This work aims at shedding some light on connections between finite state machines (FSMs), and recurrent neural networks (RNNs). Examined connections in this master's thesis is thr…
cs.LG2020★ 4 cited
Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results
Reda Marzouk, Colin de la Higuera
The need of interpreting Deep Learning (DL) models has led, during the past years, to a proliferation of works concerned by this issue. Among strategies which aim at shedding some…