Papers by Murielle Fabre

1 papers
Variable beam search for generative neural parsing and its relevance for the analysis of neuro-imaging signal (D19-1)

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Challenge: a variable beam size inference method is proposed for generative parsing for RNNG . the proposed method is not sensitive to lexical biases faced by standard beam search .
Approach: They propose a method of variable beam size inference for Recurrent Neural Network Grammar by drawing inspiration from sequential Monte-Carlo methods such as particle filtering.
Outcome: The proposed method is based on a generative parsing framework that can be used to model brain activity during online sentence comprehension.

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