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Marginal Inference queries in Hidden Markov Models under context-free grammar constraints
When the probabilistic model is sequential, more sophisticated marginal inference queries involving complex grammars may be of interest in fields such as computational linguistics and NLP.
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks
With regard to computability, new computational results on the distance and the equivalence problem between RNNs trained as language models and different types of weighted finite state machines were given.
Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results
The need of interpreting Deep Learning (DL) models has led, during the past years, to a proliferation of works concerned by this issue.
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