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2004.00478
Cited By

Distance and Equivalence between Finite State Machines and Recurrent
Neural Networks: Computational results

Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results

1 April 2020

C. D. L. Higuera

ArXiv (abs)PDF HTML

Papers citing "Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results"

4 / 4 papers shown

Extracting Weighted Automata for Approximate Minimization in Language
Modelling

Extracting Weighted Automata for Approximate Minimization in Language ModellingInternational Conference on Graphics and Interaction (GI), 2021

Prakash Panangaden

Guillaume Rabusseau

325

8

0

05 Jun 2021

Formal Language Theory Meets Modern NLP

Formal Language Theory Meets Modern NLP

William Merrill

438

17

0

19 Feb 2021

Distillation of Weighted Automata from Recurrent Neural Networks using a
Spectral Approach

Distillation of Weighted Automata from Recurrent Neural Networks using a Spectral ApproachMachine-mediated learning (ML), 2020

Stéphane Ayache

223

19

0

28 Sep 2020

On Computability, Learnability and Extractability of Finite State
Machines from Recurrent Neural Networks

On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks

218

2

0

10 Sep 2020

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