Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Knowledge extraction from the learning of sequences in a long short term
  memory (LSTM) architecture   We introduce a general method to extract knowledge from a recurrent neural
network (Long Short Term Memory) that has learnt to detect if a given input
sequence is valid or not, according to an unknown generative automaton. Based
on the clustering of the hidden states, we explain how to build and validate an
automaton that corresponds to the underlying (unknown) automaton, and allows to
predict if a given sequence is valid or not. The method is illustrated on
artificial grammars (Reber's grammar variations) as well as on a real use-case
whose underlying grammar is unknown.

25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci